Note, all of the patents, patent applications, technical papers and other references referenced below are incorporated herein by reference in their entirety unless stated otherwise.
Automobiles equipped with airbags are well known in the prior art. In such airbag systems, the car crash is sensed and the airbags rapidly inflated thereby insuring the safety of an occupation in a car crash. Many lives have now been saved by such airbag systems. However, depending on the seated state of an occupant, there are cases where his or her life cannot be saved even by present airbag systems. For example, when a passenger is seated on the front passenger seat in a position other than a forward facing, normal state, e.g., when the passenger is out of position and near the deployment door of the airbag, there will be cases when the occupant will be seriously injured or even killed by the deployment of the airbag.
Also, sometimes a child seat is placed on the passenger seat in a rear facing position and there are cases where a child sitting in such a seat has been seriously injured or killed by the deployment of the airbag.
Furthermore, in the case of a vacant seat, there is no need to deploy an airbag, and in such a case, deploying the airbag is undesirable due to a high replacement cost and possible release of toxic gases into the passenger compartment. Nevertheless, most airbag systems will deploy the airbag in a vehicle crash even if the seat is unoccupied.
Thus, whereas thousands of lives have been saved by airbags, a large number of people have also been injured, some seriously, by the deploying airbag, and over 100 people have now been killed. Thus, significant improvements need to be made to airbag systems. As discussed in detail in U.S. Pat. No. 5,653,462, for a variety of reasons vehicle occupants may be too close to the airbag before it deploys and can be seriously injured or killed as a result of the deployment thereof. Also, a child in a rear facing child seat that is placed on the right front passenger seat is in danger of being seriously injured if the passenger airbag deploys. For these reasons and, as first publicly disclosed in Breed, D. S. “How Airbags Work” presented at the International Conference on Seatbelts and Airbags in 1993 in Canada, occupant position sensing and rear facing child seat detection systems are required in order to minimize the damages caused by deploying front and side airbags. It also may be required in order to minimize the damage caused by the deployment of other types of occupant protection and/or restraint devices that might be installed in the vehicle.
For these reasons, there has been proposed an occupant sensor system also known as a seated-state detecting unit such as disclosed in the following U.S. patents assigned to the current assignee of the present application: Breed et al. (U.S. Pat. No. 5,563,462); Breed et al. (U.S. Pat. No. 5,829,782); Breed et al. (U.S. Pat. No. 5,822,707): Breed et al. (U.S. Pat. No. 5,694,320); Breed et al. (U.S. Pat. No. 5,748,473); Varga et al. (U.S. Pat. No. 5,943,295); Breed et al. (U.S. Pat. No. 6,078,854); Breed et al. (U.S. Pat. No. 6,081,757); and Breed et al. (U.S. Pat. No. 6,242,701). Typically, in some of these designs three or four sensors or sets of sensors are installed at three or four points in a vehicle for transmitting ultrasonic or electromagnetic waves toward the passenger or driver's seat and receiving the reflected waves. Using appropriate hardware and software, the approximate configuration of the occupancy of either the passenger or driver seat can be determined thereby identifying and categorizing the occupancy of the relevant seat.
These systems will solve the out-of-position occupant and the rear facing child seat problems related to current airbag systems and prevent unneeded and unwanted airbag deployments when a front seat is unoccupied. Some of the airbag systems will also protect rear seat occupants in vehicle crashes and all occupants in side impacts.
However, there is a continual need to improve the systems which detect the presence of occupants, determine if they are out-of-position and to identify the presence of a rear facing child seat in the rear seat as well as the front seat. Future automobiles are expected to have eight or more airbags as protection is sought for rear seat occupants and from side impacts. In addition to eliminating the disturbance and possible harm of unnecessary airbag deployments, the cost of replacing these airbags will be excessive if they all deploy in an accident needlessly. The improvements described below minimize this cost by not deploying an airbag for a seat, which is not occupied by a human being. An occupying item of a seat may be a living occupant such as a human being or dog, another living organism such as a plant, or an inanimate object such as a box or bag of groceries.
A child in a rear facing child seat, which is placed on the right front passenger seat, is in danger of being seriously injured if the passenger airbag deploys. This has now become an industry-wide concern and the U.S. automobile industry is continually searching for an economical solution that will prevent the deployment of the passenger side airbag if a rear facing child seat is present. The inventions disclosed herein include sophisticated apparatus to identify objects within the passenger compartment and address this concern.
The need for an occupant out-of-position sensor has also been observed by others and several methods have been described in certain U.S. patents for determining the position of an occupant of a motor vehicle. However, none of these prior art systems are capable of solving the many problems associated with occupant sensors and no prior art has been found that describe the methods of adapting such sensors to a particular vehicle model to obtain high system accuracy. Also, none of these systems employ pattern recognition technologies that are believed to be essential to accurate occupant sensing. Each of these prior are systems will be discussed below.
In 1984, the National Highway Traffic Safety Administration (NHTSA) of the U.S. Department of Transportation issued a requirement for frontal crash protection of automobile occupants known as FMVSS-208. This regulation mandated “passive occupant restraints” for all passenger cars by 1992. A further modification to FMVSS-208 required both driver and passenger side airbags on all passenger cars and light trucks by 1998. FMVSS-208 was later modified to require all vehicles to have occupant sensors. The demand for airbags is constantly accelerating in both Europe and Japan and all vehicles produced in these areas and eventually worldwide will likely be, if not already, equipped with airbags as standard equipment and eventually with occupant sensors.
A device to monitor the vehicle interior and identify its contents is needed to solve these and many other problems. For example, once a Vehicle Interior Identification and Monitoring System (VIMS) for identifying and monitoring the contents of a vehicle is in place, many other products become possible as discussed below.
Inflators now exist which will adjust the amount of gas flowing to the airbag to account for the size and position of the occupant and for the severity of the accident. The VIMS discussed in U.S. Pat. No. 5,829,782 will control such inflators based on the presence and position of vehicle occupants or of a rear facing child seat. The inventions here are improvements on that VIMS system and some use an advanced optical system comprising one or more CCD or CMOS arrays plus a source of illumination preferably combined with a trained neural network pattern recognition system.
In the early 1990's, the current assignee (ATI) developed a scanning laser radar optical occupant sensor that had the capability of creating a three dimensional image of the contents of the passenger compartment. After proving feasibility, this effort was temporarily put aside due to the high cost of the system components and the current assignee then developed an ultrasonic based occupant sensor that was commercialized and is now in production on some Jaguar models. The current assignee has long believed that optical systems would eventually become the technology of choice when the cost of optical components came down. This has now occurred and for the past several years, ATI has been developing a variety of optical occupant sensors.
The current assignee's first camera optical occupant sensing system was an adult zone-classification system that detected the position of the adult passenger. Based on the distance from the airbag, the passenger compartment was divided into three zones, namely safe-seating zone, at-risk zone, and keep-out zone. This system was implemented in a vehicle under a cooperative development program with NHTSA. This proof-of-concept was developed to handle low-light conditions only. It used three analog CMOS cameras and three near-infrared LED clusters. It also required a desktop computer with three image acquisition boards. The locations of the camera/LED modules were: the A-pillar, the IP, and near the overhead console. The system was trained to handle camera blockage situations, so that the system still functioned well even when two cameras were blocked. The processing speed of the system was close to 50 fps giving it the capability of tracking an occupant during pre-crash braking situations—that is a dynamic system.
The second camera optical system was an occupant classification system that separated adult occupants from all other situations (i.e., child, child restraint and empty seat). This system was implemented using the same hardware as the first camera optical system. It was also developed to handle low-light conditions only. The results of this proof-of-concept were also very promising.
Since the above systems functioned well even when two cameras were blocked, it was decided to develop a stand alone system that is FMVSS208-compliant, and price competitive with weight-based systems but with superior performance. Thus, a third camera optical system (for occupant classification) was developed. Unlike the earlier systems, this system used one digital CMOS camera and two high-power near-infrared LEDs. The camera/LED module was installed near the overhead console and the image data was processed using a laptop computer. This system was developed to divide the occupancy state into four classes: 1) adult; 2) child, booster seat and forward facing child seat; 3) infant carrier and rearward facing child seat; and 4) empty seat. This system included two subsystems: a nighttime subsystem for handling low-light conditions, and a daytime subsystem for handling ambient-light conditions. Although the performance of this system proved to be superior to the earlier systems, it exhibited some weakness mainly due to a non-ideal aiming direction of the camera.
Finally, a fourth camera optical system was implemented using near production intent hardware using, for example, an ECU (Electronic Control Unit) to replace the laptop computer. In this system, the remaining problems of earlier systems were overcome. The hardware in this system is not unique so the focus below will be on algorithms and software which represent the innovative heart of the system.
1. Prior Art Occupant Sensors
In White et al., (U.S. Pat. No. 5,071,160) a single acoustic sensor is described and, as illustrated, is disadvantageously mounted lower than the steering wheel. White et al. correctly perceive that such a sensor could be defeated, and the airbag falsely deployed (indicating that the system of White et al. deploys the airbag on occupant motion rather then suppressing it), by an occupant adjusting the control knobs on the radio and thus they suggest the use of a plurality of such sensors. White et al. does not disclose where such sensors would be mounted, other than on the instrument panel below the steering wheel, or how they would be combined to uniquely monitor particular locations in the passenger compartment and to identify the object(s) occupying those locations. The adaptation process to vehicles is not described nor is a combination of pattern recognition algorithms, nor any pattern recognition algorithm.
White et al. also describe the use of error correction circuitry, without defining or illustrating the circuitry, to differentiate between the velocity of one of the occupant's hands, as in the case where he/she is adjusting the knob on the radio, and the remainder of the occupant. Three ultrasonic sensors of the type disclosed by White et al. might, in some cases, accomplish this differentiation if two of them indicated that the occupant was not moving while the third was indicating that he or she was moving. Such a combination, however, would not differentiate between an occupant with both hands and arms in the path of the ultrasonic transmitter at such a location that they were blocking a substantial view of the occupant's head or chest. Since the sizes and driving positions of occupants are extremely varied, trained pattern recognition systems, such as neural networks and combinations thereof, are required when a clear view of the occupant, unimpeded by his/her extremities, cannot be guaranteed. White et al. do not suggest the use of such neural networks.
Mattes et al. (U.S. Pat. No. 5,118,134) describe a variety of methods of measuring the change in position of an occupant including ultrasonic, active or passive infrared and microwave radar sensors, and an electric eye. The sensors measure the change in position of an occupant during a crash and use that information to access the severity of the crash and thereby decide whether or not to deploy the airbag. They are thus using the occupant motion as a crash sensor. No mention is made of determining the out-of-position status of the occupant or of any of the other features of occupant monitoring as disclosed in one or more of the above-referenced patents and patent applications. Nowhere does Mattes et al. discuss how to use active or passive infrared to determine the position of the occupant. As pointed out in one or more of the above-referenced patents and patent applications, direct occupant position measurement based on passive infrared is probably not possible with a single detector and, until very recently, was very difficult and expensive with active infrared requiring the modulation of an expensive GaAs infrared laser. Since there is no mention of these problems, the method of use contemplated by Mattes et al. must be similar to the electric eye concept where position is measured indirectly as the occupant passes by a plurality of longitudinally spaced-apart sensors.
The object of an occupant out-of-position sensor is to determine the location of the head and/or chest of the vehicle occupant in the passenger compartment relative to the occupant protection apparatus, such as an airbag, since it is the impact of either the head or chest with the deploying airbag that can result in serious injuries. Both White et al. and Mattes et al. disclose only lower mounting locations of their sensors that are mounted in front of the occupant such as on the dashboard or below the steering wheel. Both such mounting locations are particularly prone to detection errors due to positioning of the occupant's hands, arms and legs. This would require at least three, and preferably more, such sensors and detectors and an appropriate logic circuitry, or pattern recognition system, which ignores readings from some sensors if such readings are inconsistent with others, for the case, for example, where the driver's arms are the closest objects to two of the sensors. The determination of the proper transducer mounting locations, aiming and field angles and pattern recognition system architectures for a particular vehicle model are not disclosed in either White et al. or Mattes et al. and are part of the vehicle model adaptation process described herein.
Fujita et al., in U.S. Pat. No. 5,074,583, describe another method of determining the position of the occupant but do not use this information to control and suppress deployment of an airbag if the occupant is out-of-position, or if a rear facing child seat is present. In fact, the closer that the occupant gets to the airbag, the faster the inflation rate of the airbag is according to the Fujita et al. patent, which thereby increases the possibility of injuring the occupant. Fujita et al. do not measure the occupant directly but instead determine his or her position indirectly from measurements of the seat position and the vertical size of the occupant relative to the seat. This occupant height is determined using an ultrasonic displacement sensor mounted directly above the occupant's head.
It is important to note that in all cases in the above-cited prior art, except those assigned to the current assignee of the instant invention, no mention is made of the method of determining transducer location, deriving the algorithms or other system parameters that allow the system to accurately identify and locate an object in the vehicle. In contrast, in one implementation of the instant invention, the return wave echo pattern corresponding to the entire portion of the passenger compartment volume of interest is analyzed from one or more transducers and sometimes combined with the output from other transducers, providing distance information to many points on the items occupying the passenger compartment.
Other patents describing occupant sensor systems include U.S. Pat. No. 5,482,314 (Corrado et al.) and U.S. Pat. No. 5,890,085 (Corrado et al.). These patents, which were filed after the initial filings of the inventions herein and thus not necessarily prior art, describe a system for sensing the presence, position and type of an occupant in a seat of a vehicle for use in enabling or disabling a related airbag activator. A preferred implementation of the system includes two or more different but collocated sensors which provide information about the occupant and this information is fused or combined in a microprocessor circuit to produce an output signal to the airbag controller. According to Corrado et al., the fusion process produces a decision as to whether to enable or disable the airbag with a higher reliability than a single phenomena sensor or non-fused multiple sensors. By fusing the information from the sensors to make a determination as to the deployment of the airbag, each sensor has only a partial effect on the ultimate deployment determination. The sensor fusion process is a crude pattern recognition process based on deriving the fusion “rules” by a trial and error process rather than by training.
The sensor fusion method of Corrado et al. requires that information from the sensors be combined prior to processing by an algorithm in the microprocessor. This combination can unnecessarily complicate the processing of the data from the sensors and other data processing methods can provide better results. For example, as discussed more fully below, it has been found to be advantageous to use a more efficient pattern recognition algorithm such as a combination of neural networks or fuzzy logic algorithms that are arranged to receive a separate stream of data from each sensor, without that data being combined with data from the other sensors (as in done in Corrado et al.) prior to analysis by the pattern recognition algorithms. In this regard, it is important to appreciate that sensor fusion is a form of pattern recognition but is not a neural network and that significant and fundamental differences exist between sensor fusion and neural networks. Thus, some embodiments of the invention described below differ from that of Corrado et al. because they include a microprocessor which is arranged to accept only a separate stream of data from each sensor such that the stream of data from the sensors are not combined with one another. Further, the microprocessor processes each separate stream of data independent of the processing of the other streams of data, that is, without the use of any fusion matrix as in Corrado et al.
1.1 Ultrasonics
The use of ultrasound for occupant sensing has many advantages and some drawbacks. It is economical in that ultrasonic transducers cost less than $1 in large quantities and the electronic circuits are relatively simple and inexpensive to manufacture. However, the speed of sound limits the rate at which the position of the occupant can be updated to approximately 7 milliseconds, which though sufficient for most cases, is marginal if the position of the occupant is to be tracked during a vehicle crash. Secondly, ultrasound waves are diffracted by changes in air density that can occur when the heater or air conditioner is operated or when there is a high-speed flow of air past the transducer. Thirdly, the resolution of ultrasound is limited by its wavelength and by the transducers, which are high Q tuned devices. Typically, this resolution is on the order of about 2 to 3 inches. Finally, the fields from ultrasonic transducers are difficult to control so that reflections from unwanted objects or surfaces add noise to the data.
Ultrasonics can be used in several configurations for monitoring the interior of a passenger compartment of an automobile as described in the above-referenced patents and patent applications and in particular in U.S. Pat. No. 5,943,295. Using the teachings here, the optimum number and location of the ultrasonic and/or optical transducers can be determined as part of the adaptation process for a particular vehicle model.
In the cases of the inventions disclosed here, as discussed in more detail below, regardless of the number of transducers used, a trained pattern recognition system is preferably used to identify and classify, and in some cases to locate, the illuminated object and its constituent parts.
The ultrasonic system is the least expensive and potentially provides less information than the optical or radar systems due to the delays resulting from the speed of sound and due to the wave length which is considerably longer than the optical (including infrared) systems. The wavelength limits the detail that can be seen by the system.
In spite of these limitations, ultrasonics can provide sufficient timely information to permit the position and velocity of an occupant to be accurately known and, when used with an appropriate pattern recognition system, it is capable of positively determining the presence of a rear facing child seat. One pattern recognition system that has been successfully used to identify a rear facing child seat employs neural networks and is similar to that described in papers by Gorman et al.
However, in the aforementioned literature using ultrasonics, the pattern of reflected ultrasonic waves from an adult occupant who may be out of position is sometimes similar to the pattern of reflected waves from a rear facing child seat. Also, it is sometimes difficult to discriminate the wave pattern of a normally seated child with the seat in a rear facing position from an empty seat with the seat in a more forward position. In other cases, the reflected wave pattern from a thin slouching adult with raised knees can be similar to that from a rear facing child seat. In still other cases, the reflected pattern from a passenger seat that is in a forward position can be similar to the reflected wave pattern from a seat containing a forward facing child seat or a child sitting on the passenger seat. In each of these cases, the prior art ultrasonic systems can suppress the deployment of an airbag when deployment is desired or, alternately, can enable deployment when deployment is not desired.
If the discrimination between these cases can be improved, then the reliability of the seated-state detecting unit can be improved and more people saved from death or serious injury. In addition, the unnecessary deployment of an airbag can be prevented.
Recently filed U.S. Pat. No. 6,411,202 (Gal et al.) describes a safety system for a vehicle including at least one sensor that receives waves from a region in an interior portion of the vehicle, which thereby defines a protected volume at least partially in front of the vehicle airbag. A processor is responsive to signals from the sensor for determining geometric data of objects in the protected volume. The teachings of this patent, which is based on ultrasonics, are fully disclosed in the prior patents of the current assignee referenced above.
1.2 Optics
Optics can be used in several configurations for monitoring the interior of a passenger compartment or exterior environment of an automobile. In one known method, a laser optical system uses a GaAs infrared laser beam to momentarily illuminate an object, occupant or child seat, in the manner as described and illustrated in FIG. 8 of U.S. Pat. No. 5,829,782 referenced above. The receiver can be a charge-coupled device or CCD or a CMOS imager to receive the reflected light. The laser can either be used in a scanning mode, or, through the use of a lens, a cone of light can be created which covers a large portion of the object. In these configurations, the light can be accurately controlled to only illuminate particular positions of interest within or around the vehicle. In the scanning mode, the receiver need only comprise a single or a few active elements while in the case of the cone of light, an array of active elements is needed. The laser system has one additional significant advantage in that the distance to the illuminated object can be determined as disclosed in the commonly owned '462 patent as also described below. When a single receiving element is used, a PIN or avalanche diode is preferred.
In a simpler case, light generated by a non-coherent light emitting diode (LED) device is used to illuminate the desired area. In this case, the area covered is not as accurately controlled and a larger CCD or CMOS array is required. Recently the cost of CCD and CMOS arrays has dropped substantially with the result that this configuration may now be the most cost-effective system for monitoring the passenger compartment as long as the distance from the transmitter to the objects is not needed. If this distance is required, then the laser system, a stereographic system, a focusing system, a combined ultrasonic and optic system, or a multiple CCD or CMOS array system as described herein is required. Alternately, a modulation system such as used with the laser distance system can be used with a CCD or CMOS camera and distance determined on a pixel by pixel basis.
As discussed above, the optical systems described herein are also applicable for many other sensing applications both inside and outside of the vehicle compartment such as for sensing crashes before they occur as described in U.S. Pat. No. 5,829,782, for a smart headlight adjustment system and for a blind spot monitor (also disclosed in U.S. patent application Ser. No. 09/851,362, now U.S. Pat. No. 7,049,945).
1.3 Ultrasonics and Optics
The laser systems described above are expensive due to the requirement that they be modulated at a high frequency if the distance from the airbag to the occupant, for example, needs to be measured. Alternately, modulation of another light source such as an LED can be done and the distance measurement accomplished using a CCD or CMOS array on a pixel by pixel basis, as discussed below.
Both laser and non-laser optical systems in general are good at determining the location of objects within the two dimensional plane of the image and a pulsed laser radar system in the scanning mode can determine the distance of each part of the image from the receiver by measuring the time of flight such as through range gating techniques. Distance can also be determined by using modulated electromagnetic radiation and measuring the phase difference between the transmitted and received waves. It is also possible to determine distance with a non-laser system by focusing, or stereographically if two spaced apart receivers are used and, in some cases, the mere location in the field of view can be used to estimate the position relative to the airbag, for example. Finally, a recently developed pulsed quantum well diode laser also provides inexpensive distance measurements as discussed in U.S. Pat. No. 6,324,453.
Acoustic systems are additionally quite effective at distance measurements since the relatively low speed of sound permits simple electronic circuits to be designed and minimal microprocessor capability is required. If a coordinate system is used where the z-axis is from the transducer to the occupant, acoustics are good at measuring z dimensions while simple optical systems using a single CCD or CMOS arrays are good at measuring x and y dimensions. The combination of acoustics and optics, therefore, permits all three measurements to be made from one location with low cost components as discussed in commonly assigned U.S. Pat. No. 5,845,000 and U.S. Pat. No. 5,835,613.
One example of a system using these ideas is an optical system which floods the passenger seat with infrared light coupled with a lens and a receiver array, e.g., CCD or CMOS array, which receives and displays the reflected light and an analog to digital converter (ADC) which digitizes the output of the CCD or CMOS and feeds it to an Artificial Neural Network (ANN) or other pattern recognition system for analysis. This system uses an ultrasonic transmitter and receiver for measuring the distances to the objects located in the passenger seat. The receiving transducer feeds its data into an ADC and from there, the converted data is directed into the ANN. The same ANN can be used for both systems thereby providing full three-dimensional data for the ANN to analyze. This system, using low cost components, will permit accurate identification and distance measurements not possible by either system acting alone. If a phased array system is added to the acoustic part of the system, the optical part can determine the location of the driver's ears, for example, and the phased array can direct a narrow beam to the location and determine the distance to the occupant's ears.
2. Adaptation
The adaptation of an occupant sensor system to a vehicle is the subject of a great deal of research and its own extensive body of knowledge as will be disclosed below. There is no significant prior art in the field with the possible exception of the descriptions of sensor fusion methods in the Corrado patents discussed above.
3. Mounting Locations for and Quantity of Transducers There is little in the literature discussed herein concerning the mounting of cameras or other imagers or transducers in the vehicle other than in the current assignee's patents referenced above. Where camera mounting is mentioned the general locations chosen are the instrument panel, roof or headliner, A-Pillar or rear view mirror. Virtually no discussion is provided as to the methodology for choosing a particular location except in the current assignee's patents.
3.1 Single Camera, Dual Camera with Single Light Source
Farmer et al. (U.S. Pat. No. 6,005,958) describes a method and system for detecting the type and position of a vehicle occupant utilizing a single camera unit. The single camera unit is positioned at the driver or passenger side A-pillar in order to generate data of the front seating area of the vehicle. The type and position of the occupant is used to optimize the efficiency and safety in controlling deployment of an occupant protection device such as an air bag.
A single camera is, naturally, the least expensive solution but suffers from the problem that there is no easy method of obtaining three-dimensional information about people or objects that are occupying the passenger compartment. A second camera can be added but to locate the same objects or features in the two images by conventional methods is computationally intensive unless the two cameras are close together. If they are close together, however, then the accuracy of the three dimensional information is compromised. Also if they are not close together, then the tendency is to add separate illumination for each camera. An alternate solution, for which there is no known prior art, is to use two cameras located at different positions in the passenger compartment but to use a single lighting source. This source can be located adjacent to one camera to minimize the installation sites. Since the LED illumination is now more expensive than the imager, the cost of the second camera does not add significantly to the system cost. The correlation of features can then be done using pattern recognition systems such as neural networks.
Two cameras also provide a significant protection from blockage and one or more additional cameras, with additional illumination, can be added to provide almost complete blockage protection.
3.2 Camera Location—Mirror, IP, Roof
The only prior art for occupant sensor location for airbag control is White et al. and Mattes et al. discussed above. Both place their sensors below or on the instrument panel. The first disclosure of the use of cameras for occupant sensing is believed to appear in the above referenced patents of the current assignee. The first disclosure of the location of a camera anywhere and especially above the instrument panel such as on the A-pillar, roof or rear view mirror also is believed to appear in the current assignee's above-referenced patents.
Corrado U.S. Pat. No. 6,318,697 discloses the placement of a camera onto a special type of rear view mirror. DeLine U.S. Pat. No. 6,124,886 also discloses the placement of a video camera on a rear view mirror for sending pictures using visible light over a cell phone. The general concept of placement of such a transducer on a mirror, among other places, is believed to have been first disclosed in commonly owned patent U.S. RE037736 which also first discloses the use of an IR camera and IR illumination that is either co-located or located separately from the camera.
3.3 Color Cameras—Multispectral Imaging
The accurate detection, categorization and eventually recognition of an object in the passenger compartment are aided by using all available information. Initial camera based systems are monochromic and use active and, in some cases, passive infrared. As microprocessors become more powerful and sensor systems improve there will be a movement to broaden the observed spectrum to the visual spectrum and then further into the mid and far infrared parts of the spectrum. There is no known literature on this at this time except that provided by the current assignee below and in proper patents.
3.4 High Dynamic Range Cameras
The prior art of high dynamic range cameras centers around the work of the Fraunhofer-Inst. of Microelectronic Circuits & Systems in Duisburg, Germany. and the Jet Propulsion Laboratory, Licensed to Photobit, and is reflected in several patents including U.S. Pat. No. 5,471,515, U.S. Pat. No. 5,608,204, U.S. Pat. No. 5,635,753, U.S. Pat. No. 5,892,541, U.S. Pat. No. 6,175,383, U.S. Pat. No. 6,215,428, U.S. Pat. No. 6,388,242, and U.S. Pat. No. 6,388,243. The current assignee is believed to be the first to recognize and apply this technology for occupant sensing as well as monitoring the environment surrounding the vehicle and thus there is not believed to be any prior art for this application of the technology.
Related to this is the work done at Columbia University by Professor Nayar as disclosed in PCT patent application WO0079784 assigned to Columbia University, which is also applicable to monitoring the interior and exterior of the vehicle. An excellent technical paper also describes this technique: Nayar, S. K. and Mitsunaga, T. “High Dynamic Range Imaging: Spatially Varying Pixel Exposures” Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, South Carolina, June 2000. Again there does not appear to be any prior art that predates the disclosure of this application of the technology by the current assignee.
A paper entitled “A 256×256 CMOS Brightness Adaptive Imaging Array with Column-Parallel Digital Output” by C. Sodini et al., 1988 IEEE International Conference on Intelligent Vehicles, describes a CMOS image sensor for intelligent transportation system applications such as adaptive cruise control and traffic monitoring. Among the purported novelties is the use of a technique for increasing the dynamic range in a CMOS imager by a factor of approximately 20, which technique is based on a previously described technique for CCD imagers.
Waxman et al. U.S. Pat. No. 5,909,244 discloses a novel high dynamic range camera that can be used in low light situations with a frame rate >25 frames per second for monitoring either the interior or exterior of a vehicle. It is suggested that this camera can be used for automotive navigation but no mention is made of its use for safety monitoring. Similarly, Savoye et al. U.S. Pat. No. 5,880,777 disclose a high dynamic range imaging system similar to that described in the '244 patent that could be employed in the inventions disclosed herein.
There are numerous technical papers of high dynamic range cameras and some recent ones discuss automotive applications, after the concept was first discussed in the current assignee's patents and patent applications. One recent example is T. Lulé1, H. Keller1, M. Wagner1, M. Böhm, C. D. Hamann, L. Humm, U. Efron, “100.000 Pixel 120 dB Imager for Automotive Vision”, presented in the Proceedings of the Conference on Advanced Microsystems for Automotive Applications (AMAA), Berlin, 18./19, Mar. 1999. This paper discusses the desirability of a high dynamic range camera and points out that an integration based method is preferable to a logarithmic system in that greater contrast is potentially obtained. This brings up the question as to what dynamic range is really needed. The current assignee has considered desiring a high dynamic range camera but after more careful consideration, it is really the dynamic range within a given image that is important and that is usually substantially below 120 db, and in fact, a standard 70+ db camera is fine for most purposes.
As long as the shutter or an iris can be controlled to chose where the dynamic range starts, then, for night imaging a source of illumination is generally used and for imaging in daylight the shutter time or iris can be substantially controlled to provide an adequate image. For those few cases where there is a very bright sunlight entering the vehicle's window but the interior is otherwise in shade, multiple exposures can provide the desired contrast as taught by Nayar and discussed above. This is not to say that a high dynamic range camera is inherently bad, just to illustrate that there are many technologies that can be used to accomplish the same goal.
3.5 Fisheye Lens, Pan and Zoom
There is significant prior art on the use of a fisheye or similar high viewing angle lens and a non-moving pan, tilt, rotation and zoom cameras however there appears to be no prior art on the application of these technologies to sensing inside or outside of the vehicle prior to the disclosure by the current assignee. One significant patent is U.S. Pat. No. 5,185,667 to Zimmermann. For some applications, the use of a fisheye type lens can significantly reduce the number of imaging devices that are required to monitor the interior or exterior of a vehicle. An important point is that whereas for human viewing, the images are usually mathematically corrected to provide a recognizable view, when a pattern recognition system such as a neural network is used, it is frequently not necessary to perform this correction, thus simplifying the analysis.
Recently, a paper has been published that describes the fisheye camera system disclosed years ago by the current assignee: V. Ramesh, M. Greiffenhagen, S. Boverie, A. Giratt, “Real-Time Surveillance and Monitoring for Automotive Applications”, SAE 2000-01-0347.
4. 3D Cameras
4.1 Stereo
European Patent Application No. EP0885782A1 describes a purportedly novel motor vehicle control system including a pair of cameras which operatively produce first and second images of a passenger area. A distance processor determines the distances that a plurality of features in the first and second images are from the cameras based on the amount that each feature is shifted between the first and second images. An analyzer processes the determined distances and determines the size of an object on the seat. Additional analysis of the distance also may determine movement of the object and the rate of movement. The distance information also can be used to recognize predefined patterns in the images and thus identify objects. An air bag controller utilizes the determined object characteristics in controlling deployment of the air bag.
Simoncelli in U.S. Pat. No. 5,703,677 discloses an apparatus and method using a single lens and single camera with a pair of masks to obtain three dimensional information about a scene.
A paper entitled “Sensing Automobile Occupant Position with Optical Triangulation” by W. Chappelle, Sensors, December 1995, describes the use of optical triangulation techniques for determining the presence and position of people or rear-facing infant seats in the passenger compartment of a vehicle in order to guarantee the safe deployment of an air bag. The paper describes a system called the “Takata Safety Shield” which purportedly makes high-speed distance measurements from the point of air bag deployment using a modulated infrared beam projected from an LED source. Two detectors are provided, each consisting of an imaging lens and a position-sensing detector.
A paper entitled “An Interior Compartment Protection System based on Motion Detection Using CMOS Imagers” by S. B. Park et al., 1998 IEEE International Conference on Intelligent Vehicles, describes a purportedly novel image processing system based on a CMOS image sensor installed at the car roof for interior compartment monitoring including theft prevention and object recognition. One disclosed camera system is based on a CMOS image sensor and a near infrared (NIR) light emitting diode (LED) array.
Krumm (U.S. Pat. No. 5,983,147) describes a system for determining the occupancy of a passenger compartment including a pair of cameras mounted so as to obtain binocular stereo images of the same location in the passenger compartment. A representation of the output from the cameras is compared to stored representations of known occupants and occupancy situations to determine which stored representation the output from the cameras most closely approximates. The stored representations include that of the presence or absence of a person or an infant seat in the front passenger seat.
4.2 Distance by Focusing
A focusing system, such as used on some camera systems, can be used to determine the initial position of an occupant but, in most cases, it is too slow to monitor his position during a crash. This is a result of the mechanical motions required to operate the lens focusing system, however, methods do exist that do not require mechanical motions. By itself, it cannot determine the presence of a rear facing child seat or of an occupant but when used with a charge-coupled or CMOS device plus some infrared illumination for vision at night, and an appropriate pattern recognition system, this becomes possible. Similarly, the use of three dimensional cameras based on modulated waves or range-gated pulsed light methods combined with pattern recognition systems are now possible based on the teachings of the inventions disclosed herein and the commonly assigned patents and patent applications referenced above.
U.S. Pat. No. 6,198,998 to Farmer discloses a single IR camera mounted on the A-Pillar where a side view of the contents of the passenger compartment can be obtained. A sort of three dimensional view is obtained by using a narrow depth of focus lens and a de-blurring filter. IR is used to illuminate the volume and the use of a pattern on the LED to create a sort of structured light is also disclosed. Pattern recognition by correlation is also discussed.
U.S. Pat. No. 6,229,134 to Nayar et al. is an excellent example of the determination of the three-dimensional shape of a object using active blurring and focusing methods. The use of structured light is also disclosed in this patent. The method uses illumination of the scene with a pattern and two images of the scene are sensed with different imaging parameters.
A mechanical focusing system, such as used on some camera systems, can determine the initial position of an occupant but is currently too slow to monitor his/her position during a crash or even during pre-crash braking. Although the example of an occupant is used here as an example, the same or similar principles apply to objects exterior to the vehicle. A distance measuring system based on focusing is described in U.S. Pat. No. 5,193,124 and U.S. Pat. No. 5,231,443 (Subbarao) that can either be used with a mechanical focusing system or with two cameras, the latter of which would be fast enough to allow tracking of an occupant during pre-crash braking and perhaps even during a crash depending on the field of view that is analyzed. Although the Subbarao patents provide a good discussion of the camera focusing art, it is a more complicated system than is needed for practicing the instant inventions. In fact, a neural network can also be trained to perform the distance determination based on the two images taken with different camera settings or from two adjacent CCD's and lens having different properties as the cameras disclosed in Subbarao making this technique practical for the purposes herein. Distance can also be determined by the system disclosed in U.S. Pat. No. 5,003,166 (Girod) by spreading or defocusing a pattern of structured light projected onto the object of interest. Distance can also be measured by using time of flight measurements of the electromagnetic waves or by multiple CCD or CMOS arrays as is a principle teaching of this invention.
Dowski, Jr. in U.S. Pat. No. 5,227,890 provides an automatic focusing system for video cameras which can be used to determine distance and thus enable the creation of a three dimensional image.
A good description of a camera focusing system is found in G. Zorpette, “Focusing in a flash”, Scientific American August 2000.
In each of these cases, regardless of the distance measurement system used, a trained pattern recognition system, as defined above, can be used to identify and classify, and in some cases to locate, the illuminated object and its constituent parts.
4.3 Ranging
Cameras can be used for obtaining three dimensional images by modulation of the illumination as described in U.S. Pat. No. 5,162,861. The use of a ranging device for occupant sensing is believed to have been first disclosed by the current assignee in the patents mentioned herein. More recent attempts include the PMD camera as disclosed in PCT application WO09810255 and similar concepts disclosed in U.S. Pat. No. 6,057,909 and U.S. Pat. No. 6,100,517.
A paper by Rudolf Schwarte, et al. entitled “New Powerful Sensory Tool in Automotive Safety Systems Based on PMD-Technology”, Eds. S. Krueger, W. Gessner, Proceedings of the AMAA 2000 Advanced Microsystems for Automotive Applications 2000, Springer Verlag; Berlin, Heidelberg, New York, ISBN 3-540-67087-4, describes an implementation of the teachings of the instant invention wherein a modulated light source is used in conjunction with phase determination circuitry to locate the distance to objects in the image on a pixel by pixel basis. This camera is an active pixel camera the use of which for internal and external vehicle monitoring is also a teaching of this invention. The novel feature of the PMD camera is that the pixels are designed to provide a distance measuring capability within each pixel itself. This then is a novel application of the active pixel and distance measuring teachings of the instant invention.
The paper “Camera Records color and Depth”, Laser Focus World, Vol. 36 No. 7 July 2000, describes another method of using modulated light to measure distance.
“Seeing distances-a fast time-of-flight 3D camera ”, Sensor Review Vol. 20 No. 3 2000, presents a time-of-flight camera that also can be used for internal and external monitoring. Similarly, see “Electro-optical correlation arrangement for fast 3D cameras: properties and facilities of the electro-optical mixer device”, SPIE Vol. 3100, 1997 pp. 254-60. A significant improvement to the PMD technology and to all distance by modulation technologies is to modulate with a code, which can be random or pseudo random, that permits accurate distance measurements over a long range using correlation or other technology. There is a question as to whether there is a need to individually modulate each pixel with the sent signal since the same effect can be achieved using a known Pockel or Kerr cell that covers the entire imager, which should be simpler.
The instant invention as described in the above-referenced commonly assigned patents and patent applications, teaches the use of modulating the light used to illuminate an object and to determine the distance to that object based on the phase difference between the reflected radiation and the transmitted radiation. The illumination can be modulated at a single frequency when short distances such as within the passenger compartment are to be measured. Typically, the modulation wavelength would be selected such that one wave would have a length of approximately one meter or less. This would provide resolution of 1 cm or less.
For larger vehicles, a longer wavelength would be desirable. For measuring longer distances, the illumination can be modulated at more than one frequency to eliminate cycle ambiguity if there is more than one cycle between the source of illumination and the illuminated object. This technique is particularly desirable when monitoring objects exterior to the vehicle to permit accurate measurements of devices that are hundreds of meters from the vehicle as well as those that are a few meters away. Naturally, there are other modulation methods that eliminate the cycle ambiguity such as modulation with a code that is used with a correlation function to determine the phase shift or time delay. This code can be a pseudo random number in order to permit the unambiguous monitoring of the vehicle exterior in the presence of other vehicles with the same system. This is sometimes known as noise radar, noise modulation (either of optical or radar signals), ultra wideband (UWB) or the techniques used in Micropower impulse radar (MIR). Another key advantage is to permit the separation of signals from multiple vehicles.
Although a simple frequency modulation scheme has been disclosed so far, it is also possible to use other coding techniques including the coding of the illumination with one of a variety of correlation patterns including a pseudo-random code. Similarly, although frequency and code domain systems have been described, time domain systems are also applicable wherein a pulse of light is emitted and the time of flight measured. Additionally, in the frequency domain case, a chirp can be emitted and the reflected light compared in frequency with the chirp to determine the distance to the object by frequency difference. Although each of these techniques is known to those skilled in the art, they have heretofore not been believed to have applied for monitoring objects within or outside of a vehicle.
4.4 Pockel or Kerr Cells for Determining Range
The technology for modulating a light valve or electronic shutter has been known for many years and is sometimes referred to as a Kerr cell or a Pockel cell. These devices are capable of being modulated at up to 10 billion cycles per second. For determining the distance to an occupant or his or her features, modulations between 100 and 500 MHz are needed. The higher the modulation frequency, the more accurate the distance to the object can be determined. However, if more than one wavelength, or better one-quarter wavelength, exists between the camera and the object, then ambiguities result. On the other hand, once a longer wavelength has ascertained the approximate location of the feature, then more accurate determinations can be made by increasing the modulation frequency since the ambiguity will now have been removed. In practice, only a single frequency is used of about 300 MHz. This gives a wavelength of 1 meter, which can allow cm level distance determinations.
In one preferred embodiment of this invention therefore, an infrared LED is modulated at a frequency between 100 and 500 MHz and the returning light passes through a light valve such that amount of light that impinges on the CMOS array pixels is determined by a phase difference between the light valve and the reflected light. By modulating a light valve for one frame and leaving the light valve transparent for a subsequent frame, the range to every point in the camera field of view can be determined based on the relative brightness of the corresponding pixels.
Once the range to all of the pixels in the camera view has been determined, range-gating becomes a simple mathematical exercise and permits objects in the image to be easily separated for feature extraction processing. In this manner, many objects in the passenger compartment can be separated and identified independently.
Noise, pseudo noise or code modulation techniques can be used in place of the frequency modulation discussed above. This can be in the form of frequency, amplitude or pulse modulation.
No prior art is believed to exist on this concept.
4.5 Thin Film on ASIC (TFA)
Thin film on ASIC technology, as described in Lake, D. W. “TFA Technology: The Coming Revolution in Photography”, Advanced Imaging Magazine, April, 2002 (WWW.ADVANCEDIMAGINGMAG.COM) shows promise of being the next generation of imager for automotive applications. The anticipated specifications for this technology, as reported in the Lake article, are:
Dynamic Range120dbSensitivity0.01 luxAnti-blooming1,000,000:1Pixel Density3,200,000Pixel Size3.5 umFrame Rate30 fpsDC Voltage1.8 vCompression500 to 1
All of these specifications, except for the frame rate, are attractive for occupant sensing. It is believed that the frame rate can be improved with subsequent generations of the technology. Some advantages of this technology for occupant sensing include the possibility of obtaining a three dimensional image by varying the pixel in time in relation to a modulated illumination in a simpler manner than proposed with the PMD imager or with a Pockel or Kerr cell. The ability to build the entire package on one chip will reduce the cost of this imager compared with two or more chips required by current technology.
Other technical papers on TFA include: (1) M. Böhm “Imagers Using Amorphous Silicon Thin Film on ASIC (TFA) Technology”, Journal of Non-Crystalline Solids, 266-269, pp. 1145-1151, 2000; (2) A. Eckhardt, F. Blecher, B. Schneider, J. Sterzel, S. Benthien, H. Keller, T. Lulé, P. Rieve, M. Sommer, K. Seibel, F. Mutze, M. Böhm, “Image Sensors in TFA (Thin Film on ASIC) Technology with Analog Image Pre-Processing”, H. Reichl, E. Obermeier (eds.), Proc. Micro System Technologies 98, Potsdam, Germany, pp. 165-170, 1998.; (3)T. Lulé, B. Schneider, M. Böhm, “Design and Fabrication of a High Dynamic Range Image Sensor in TFA Technology”, invited paper for IEEE Journal of Solid-State Circuits, Special Issue on 1998 Symposium on VLSI Circuits, 1999. (4) M. Böhm, F. Blecher, A. Eckhardt, B. Schneider, S. Benthien, H. Keller, T. Lulé, P. Rieve, M. Sommer, R. C. Lind, L. Humm, M. Daniels, N. Wu, H. Yen, “High Dynamic Range Image Sensors in Thin Film on ASIC—Technology for Automotive Applications”, D. E. Ricken, W. Gessner (eds.), Advanced Microsystems for Automotive Applications, Springer-Verlag, Berlin, pp. 157-172, 1998. (5) M. Böhm, F. Blecher, A. Eckhardt, K. Seibel, B. Schneider, J. Sterzel, S. Benthien, H. Keller, T. Lulé, P. Rieve, M. Sommer, B. Van Uffel, F Librecht, R. C. Lind, L. Humm, U. Efron, E. Rtoh, “Image Sensors in TFA Technology—Status and Future Trends”, Mat. Res. Soc. Symp. Proc., vol. 507, pp. 327-338, 1998.
5. Glare Control
U.S. Pat. No. 5,298,732 and U.S. Pat. No. 5,714,751 to Chen concentrate on locating the eyes of the driver so as to position a light filter between a light source such as the sun or the lights of an oncoming vehicle, and the driver's eyes. This patent will be discussed in more detail below. U.S. Pat. No. 5,305,012 to Faris also describes a system for reducing the glare from the headlights of an oncoming vehicle and it is discussed in more detail below.
5.1 Windshield
Using an advanced occupant sensor, as explained below, the position of the driver's eyes can be accurately determined and portions of the windshield, or of a special visor, can be selectively darkened to eliminate the glare from the sun or oncoming vehicle headlights. This system can use electro-chromic glass, a liquid crystal device, Xerox Gyricon, Research Frontiers SPD, semiconducting and metallic (organic) polymer displays, spatial light monitors, electronic “Venetian blinds”, electronic polarizers or other appropriate technology, and, in some cases, detectors to detect the direction of the offending light source. In addition to eliminating the glare, the standard sun visor can now also be eliminated. Alternately, the glare filter can be placed in another device such as a transparent sun visor that is placed between the driver's eyes and the windshield.
There is no known prior art that places a filter in the windshield. All known designs use an auxiliary system such as a liquid crystal panel that acts like a light valve on a pixel by pixel basis.
A description of SPD can be found at SmartGlass.com and in “New ‘Smart’ glass darkens, lightens in a flash”, Automotive News Aug. 21, 1998.
5.2 Rear View Mirrors
There is no known prior art that places a pixel addressable filter in a rear view mirror to selectively block glare or for any other purpose.
5.3 Visor for Glare Control and HUD
The prior art of this application includes U.S. Pat. No. 4,874,938, U.S. Pat. No. 5,298,732, U.S. Pat. No. 5,305,012 and U.S. Pat. No. 5,714,715.
6. Weight Measurement and Biometrics
Prior art systems are now being used to identify the vehicle occupant based on a coded key or other object carried by the occupant. This requires special sensors within the vehicle to recognize the coded object. Also, the system only works if the particular person for whom the vehicle was programmed uses the coded object. If a son or daughter, for example, who is using their mother's key, uses the vehicle then the wrong seat, mirror, radio station etc. adjustments are made. Also, these systems preserve the choice of seat position without any regard for the correctness of the seat position. With the problems associated with the 4-way seats, it is unlikely that the occupant ever properly adjusts the seat. Therefore, the error will be repeated every time the occupant uses the vehicle.
These coded systems are a crude attempt to identify the occupant. An improvement can be made if the morphological (or biological) characteristics of the occupant can be measured as described herein. Such measurements can be made of the height and weight, for example, and used not only to adjust a vehicular component to a proper position but also to remember that position, as fine tuned by the occupant, for re-positioning the component the next time the occupant occupies the seat. No prior art is believed to exist on this aspect of the invention. Additional biometrics includes physical and behavioral responses of the eyes, hands, face and voice. Iris and retinal scans are discussed in the literature but the shape of the eyes or hands, structure of the face or hands, how a person blinks or squints, the shape of the hands, how he or she grasps the steering wheel, the electrical conductivity or dielectric constant, blood vessel pattern in the hands, fingers, face or elsewhere, the temperature and temperature differences of different areas of the body are among the many biometric variables that can be measures to identify an authorized user of a vehicle, for example.
As discussed more fully below, in a preferred implementation, once at least one and preferably two of the morphological characteristics of a driver are determined, for example by measuring his or her height and weight, the component such as the seat can be adjusted and other features or components can be incorporated into the system including, for example, the automatic adjustment of the rear view and/or side mirrors based on seat position and occupant height. In addition, a determination of an out-of-position occupant can be made and based thereon, airbag deployment suppressed if the occupant is more likely to be injured by the airbag than by the accident without the protection of the airbag. Furthermore, the characteristics of the airbag including the amount of gas produced by the inflator and the size of the airbag exit orifices can be adjusted to provide better protection for small lightweight occupants as well as large, heavy people. Even the direction of the airbag deployment can, in some cases, be controlled. The prior art is limited to airbag suppression as disclosed in Mattes (U.S. Pat. No. 5,118,134) and White (U.S. Pat. No. 5,071,160) discussed above.
Still other features or components can now be adjusted based on the measured occupant morphology as well as the fact that the occupant can now be identified. Some of these features or components include the adjustment of seat armrest, cup holder, steering wheel (angle and telescoping), pedals, phone location and for that matter the adjustment of all things in the vehicle which a person must reach or interact with. Some items that depend on personal preferences can also be automatically adjusted including the radio station, temperature, ride and others.
6.1 Strain Gage Weight Sensors
Heretofore, various methods have been proposed for measuring the weight of an occupying item of a vehicular seat. The methods include pads, sheets or films that have placed in the seat cushion which attempt to measure the pressure distribution of the occupying item. Prior to its first disclosure in Breed et al. (U.S. Pat. No. 5,822,707) referenced above by the current assignee, systems for measuring occupant weight based on the strain in the seat structure had not been considered. Prior art weight measurement systems have been notoriously inaccurate. Thus, a more accurate weight measuring system is desirable. The strain measurement systems described herein, substantially eliminate the inaccuracy problems of prior art systems and permit an accurate determination of the weight of the occupying item of the vehicle seat. Additionally, as disclosed herein, in many cases, sufficient information can be obtained for the control of a vehicle component without the necessity of determining the entire weight of the occupant. For example, the force that the occupant exerts on one of the three support members may be sufficient.
6.2 Bladder Weight Sensors
Similarly to strain gage weight sensors, the first disclosure of weight sensors based of the pressure in a bladder in or under the seat cushion is believed to have been made in Breed et al. (U.S. Pat. No. 5,822,707) by the current assignee.
6.3 Combined Spatial and Weight Sensors
The combination of a weight sensor with a spatial sensor, such as the wave or electric field sensors discussed herein, permits the most accurate determination of the airbag requirements when the crash sensor output is also considered. There is not believed to be any prior art of such a combination.
6.4 Face Recognition (Face and Iris IR Scans)
Ishikawa et al. (U.S. Pat. No. 4,625,329) describes an image analyzer (M5 in FIG. 1) for analyzing the position of driver including an infrared light source which illuminates the driver's face and an image detector which receives light from the driver's face, determines the position of facial feature, e.g., the eyes in three dimensions, and thus determines the position of the driver in three dimensions. A pattern recognition process is used to determine the position of the facial features and entails converting the pixels forming the image to either black or white based on intensity and conducting an analysis based on the white area in order to find the largest contiguous white area and the center point thereof. Based on the location of the center point of the largest contiguous white area, the driver's height is derived and a heads-up display is adjusted so information is within driver's field of view. The pattern recognition process can be applied to detect the eyes, mouth, or nose of the driver based on the differentiation between the white and black areas. Ishikawa does not attempt to recognize the driver.
Ando (U.S. Pat. No. 5,008,946) describes a system which recognizes an image and specifically ascertains the position of the pupils and mouth of the occupant to enable movement of the pupils and mouth to control electrical devices installed in the automobile. The system includes a camera which takes a picture of the occupant and applies algorithms based on pattern recognition techniques to analyze the picture, converted into an electrical signal, to determine the position of certain portions of the image, namely the pupils and mouth. Ando also does not attempt to recognize the driver.
Puma (U.S. Pat. No. 5,729,619) describes apparatus and methods for determining the identity of a vehicle operator and whether he or she is intoxicated or falling asleep. Puma uses an iris scan as the identification method and thus requires the driver to place his eyes in a particular position relative to the camera. Intoxication is determined by monitoring the spectral emission from the driver's eyes and drowsiness is determined by monitoring a variety of behaviors of the driver. The identification of the driver by any means is believed to have been first disclosed in the current assignee's patents referenced above as was identifying the impairment of the driver whether by alcohol, drugs or drowsiness through monitoring driver behavior and using pattern recognition. Puma uses pattern recognition but not neural networks although correlation analysis is implied as also taught in the current assignee's prior patents.
Other patents on eye tracking include Moran et al. (U.S. Pat. No. 4,847,486) and Hutchinson (U.S. Pat. No. 4,950,069). In Moran, a scanner is used to project a beam onto the eyes of the person and the reflection from the retina through the cornea is monitored to measure the time that the person's eyes are closed. In Hutchinson, the eye of a computer operator is illuminated with light from an infrared LED and the reflected light causes bright eye effect which outlines the pupil as brighter then the rest of the eye and also causes an even brighter reflection from the cornea. By observing this reflection in the camera's field of view, the direction that the eye is pointing can be determined. In this manner, the motion of the eye can control operation of the computer. Similarly, such apparatus can be used to control various functions within the vehicle such as the telephone, radio, and heating and air conditioning.
U.S. Pat. No. 5,867,587 to Aboutalib et al. also describes a drowsy driver detection unit based on the frequency of eyeblinks where an eye blink is determined by correlation analysis with averaged previous states of the eye. U.S. Pat. No. 6,082,858 to Grace describes the use of two frequencies of light to monitor the eyes, one that is totally absorbed by the eye (950 nm) and another that is not and where both are equally reflected by the rest of the face. Thus, subtraction leaves only the eyes. An alternative, not disclosed by Aboutalib et al. or Grace, is to use natural light or a broad frequency spectrum and a filter to filter out all frequencies except 950 nm and then to proportion the intensities. U.S. Pat. No. 6,097,295 to Griesinger also attempts to determine the alertness of the driver by monitoring the pupil size and the eye shutting frequency. U.S. Pat. No. 6,091,334 uses measurements of saccade frequency, saccade speed, and blinking measurements to determine drowsiness. No attempt is made in any of these patents to locate the driver in the vehicle.
There are numerous technical papers on eye location and tracking developed for uses other than automotive including: (1) “Eye Tracking in Advanced Interface Design”, Robert J. K. Jacob, Human-Computer Interaction Lab, Naval Research Laboratory, Washington, D.C.; (2) F. Smeraldi, O. Carmona, J. Bigün, “Saccadic search with Gabor features applied to eye detection and real-time head tracking”, Image and Vision Computing 18 (2000) 323-329, Elsevier; (2) Y. Wang, B. Yuan, “Human Eyes Location Using Wavelet and Neural Networks”, Proceedings of ICSP2000, IEEE. (3) S. A. Sirohey, A. Rosenfeld, “Eye detection in a face image using linear and nonlinear filters”, Pattern Recognition 34 (2001) 1367-1391, Pergamon.
There are also numerous technical papers on human face recognition including: (1) “Pattern Recognition with Fast Feature Extractions”, M. G. Nakhodkin, Y. S. Musatenko, and V. N. Kurashov, Optical Memory and Neural Networks, Vol. 6, No. 3, 1997; (2) C. Beumier, M. Acheroy “Automatic 3D Face Recognition”, Image and Vision Computing, 18 (2000) 315-321, Elsevier.
Since the direction of gaze of the eyes is quite precise and relatively easily measured, it can be used to control many functions in the vehicle such as the telephone, lights, windows, HVAC, navigation and route guidance system, and telematics among others. Many of these functions can be combined with a heads-up display and the eye gaze can replace the mouse in selecting many functions and among many choices. It can also be combined with an accurate mapping system to display on a convenient display the writing on a sign that might be hard to read such as a street sign. It can even display the street name when a sign is not present. A gaze at a building can elicit a response providing the address of the building or some information about the building which can be provided either orally or visually. Looking at the speedometer can elicit a response as the local speed limit and looking at the fuel gage can elicit the location of the nearest gas station. None of these functions appear in the prior art discussed above.
6.5 Heartbeat and Health State
Although the concept of measuring the heartbeat of a vehicle occupant originated with the patents of the current assignee, Bader in U.S. Pat. No. 6,195,008 uses a comparison of the heartbeat with stored data to determine the age of the occupant. Other uses of heartbeat measurement include determining the presence of an occupant on a particular seat, the determination of the total number of vehicle occupants, the presence of an occupant in a vehicle for security purposes, for example, and the presence of an occupant in the trunk etc.
7. Illumination
7.1 Infrared Light
In a passive infrared system, as described in Corrado referenced above, for example, a detector receives infrared radiation from an object in its field of view, in this case the vehicle occupant, and determines the presence and temperature of the occupant based on the infrared radiation. The occupant sensor system can then respond to the temperature of the occupant, which can either be a child in a rear facing child seat or a normally seated occupant, to control some other system. This technology could provide input data to a pattern recognition system but it has limitations related to temperature.
The sensing of the child could pose a problem if the child is covered with blankets, depending on the IR frequency used. It also might not be possible to differentiate between a rear facing child seat and a forward facing child seat. In all cases, the technology can fail to detect the occupant if the ambient temperature reaches body temperature as it does in hot climates. Nevertheless, for use in the control of the vehicle climate, for example, a passive infrared system that permits an accurate measurement of each occupant's temperature is useful. Prior art systems are limited to single pixel devices. Use of an IR imager removes many of the problems listed above and is novel to the inventions disclosed herein.
In a laser optical system, an infrared laser beam is used to momentarily illuminate an object, occupant or child seat in the manner as described, and illustrated in FIG. 8, of Breed et al. (U.S. Pat. No. 5,653,462) cross-referenced above. In some cases, a CCD or a CMOS device is used to receive the reflected light. In other cases when a scanning laser is used, a pin or avalanche diode or other photo detector can be used. The laser can either be used in a scanning mode, or, through the use of a lens, a cone of light, swept line of light, or a pattern or structured light can be created which covers a large portion of the object. Additionally, one or more LEDs can be used as a light source. Also triangulation can be used in conjunction with an offset scanning laser to determine the range of the illuminated spot from the light detector. Various focusing systems also can have applicability in some implementations to measure the distance to an occupant. In most cases, a pattern recognition system, as defined herein, is used to identify, ascertain the identity of and classify, and can be used to locate and determine the position of, the illuminated object and/or its constituent parts.
The optical systems generally provide the most information about the object and at a rapid data rate. Its main drawback is cost which is usually above that of ultrasonic or passive infrared systems. As the cost of lasers and imagers comes down in the future, this system will become more competitive. Depending on the implementation of the system, there may be some concern for the safety of the occupant if a laser light can enter the occupant's eyes. This is minimized if the laser operates in the infrared spectrum particularly at the “eye-safe” frequencies.
Another important feature is that the brightness of the point of light from the laser, if it is in the infrared part of the spectrum and if a filter is used on the receiving detector, can overpower the sun with the result that the same classification algorithms can be made to work both at night and under bright sunlight in a convertible. An alternative approach is to use different algorithms for different lighting conditions.
Although active and passive infrared light has been disclosed in the prior art, the use of a scanning laser, modulated light, filters, trainable pattern recognition etc. is believed to have been first disclosed by the current assignee in the above-referenced patents.
7.2 Structured Light
U.S. Pat. No. 5,003,166 provides an excellent treatise on the use of structured light for range mapping of objects in general. It does not apply this technique for automotive applications and in particular for occupant sensing or monitoring inside or outside of a vehicle. The use of structured light in the automotive environment and particularly for sensing occupants is believed to have been first disclosed by the current assignee in the above-referenced patents.
U.S. Pat. No. 6,049,757 to Nakajima et al. describes structured light in the form of bright spots that illuminate the face of the driver to determine the inclination of the face and to issue a warning if the inclination is indicative of a dangerous situation. In the patents to the current assignee, structured light is disclosed to obtain a determination of the location of an occupant and/or his or her parts. This includes the position of any part of the occupant including the occupant's face and thus the invention of this patent is believed to be anticipated by the current assignee's patents referenced above.
U.S. Pat. No. 6,298,311 to Griffin et al. repeats much of the teachings of the early patents of the current assignee. A plurality of IR beams are modulated and directed in the vicinity of the passenger seat and used through a photosensitive receiver to detect the presence and location of an object in the passenger seat, although the particular pattern recognition system is not disclosed. The pattern of IR beams used in this patent is a form of structured light.
Structured light is also discussed in numerous technical papers for other purposes than vehicle interior or exterior monitoring including: (1) “3D Shape Recovery and Registration Based on the Projection of Non-Coherent Structured Light” by Roberto Rodella and Giovanna Sansoni, INFM and Dept. of Electronics for the Automation, University of Brescia, Via Branze 38, 1-25123 Brescia-Italy; and (2) “A Low-Cost Range Finder using a Visually Located, Structured Light Source”, R. B. Fisher, A. P. Ashbrook, C. Robertson, N. Werghi, Division of Informatics, Edinburgh University, 5 Forrest Hill, Edinburgh EHI 2QL. (3) F. Lerasle, J. Lequellec, M Devy, “Relaxation vs Maximal Cliques Search for Projected Beams Labeling in a Structured Light Sensor”, Proceedings of the International Conference on Pattern Recognition, 2000 IEEE. (4) D. Caspi, N. Kiryati, and J. Shamir, “Range Imaging With Adaptive Color Structured Light”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, No. 5, May 1998.
Recently, a paper has been published that describes a structured light camera system disclosed years ago by the current assignee: V. Ramesh, M. Greiffenhagen, S. Boverie, A. Giratt, “Real-Time Surveillance and Monitoring for Automotive Applications”, SAE 2000-01-0347.
7.3 Color and Natural Light
A number of systems have been disclosed that use illumination as the basis for occupant detection. The problem with artificial illumination is that it will not always overpower the sun and thus in a convertible on a bright sunny day, for example, the artificial light can be undetectable unless it is a point. If one or more points of light are not the illumination of choice, then the system must also be able to operate under natural light. The inventions herein accomplish the feat of accurate identification and tracking of an occupant under all lighting conditions by using artificial illumination at night and natural light when it is available. This requires that the pattern recognition system be modular with different modules used for different situations as discussed in more detail below. There is no known prior art for using natural radiation for occupant sensing systems.
When natural illumination is used, a great deal of useful information can be obtained if various parts of the electromagnetic spectrum are used. The ability to locate the face and facial features is enhanced if color is used, for example. Once again, there is no known prior art for the use of color, for example. All known systems that use electromagnetic radiation are monochromatic.
7.4 Radar
The radar portion of the electromagnetic spectrum can also be used for occupant detection as first disclosed by the current assignee in the above-referenced patents. Radar systems have similar properties to the laser system discussed above except the ability to focus the beam, which is limited in radar by the frequency chosen and the antenna size. It is also much more difficult to achieve a scanning system for the same reasons. The wavelength of a particular radar system can limit the ability of the pattern recognition system to detect object features smaller than a certain size. Once again, however, there is some concern about the health effects of radar on children and other occupants. This concern is expressed in various reports available from the United States Food and Drug Administration, Division of Devices.
When the occupying item is human, in some instances the information about the occupying item can be the occupant's position, size and/or weight. Each of these properties can have an effect on the control criteria of the component. One system for determining a deployment force of an air bag system in described in U.S. Pat. No. 6,199,904 (Dosdall). This system provides a reflective surface in the vehicle seat that reflects microwaves transmitted from a microwave emitter. The position, size and weight of a human occupant are said to be determined by calibrating the microwaves detected by a detector after the microwaves have been reflected from the reflective surface and pass through the occupant. Although some features disclosed in the '904 patent are not disclosed in the current assignee's above-referenced patents, the use of radar in general for occupant sensing is disclosed in those patents.
7.5 Frequency or Spectrum Considerations
As discussed above, it is desirable to obtain information about an occupying item in a vehicle in order to control a component in the vehicle based on the characteristics of the occupying item. For example, if it were known that the occupying item is inanimate, an airbag deployment system would generally be controlled to suppress deployment of any airbags designed to protect passengers seated at the location of the inanimate object.
Particular parts of the electromagnetic spectrum interact with animal bodies in a manner differently from inanimate objects and allow the positive identification that there is an animal in the passenger compartment, or in the vicinity of the vehicle. The choice of frequencies for both active and passive observation of people is discussed in detail in Richards, A. Alien Vision, Exploring the Electromagnetic Spectrum with Imaging Technology, 2001, SPIE Press Bellingham, Wash. In particular, in the near IR range (˜850 nm), the eyes of a person at night are easily seen when illuminated. In the near UV range (˜360 nm), distinctive skin patterns are observable that can be used for identification. In the SWIR range (1100-2500 nm), the person can be easily separated from the background.
The MWIR range (2.5-7 Microns) in the passive case clearly shows people against a cooler background except when the ambient temperature is high and then everything radiates or reflects energy in that range. However, windows are not transparent to MWIR and thus energy emitted from outside the vehicle does not interfere with the energy emitted from the occupants. This range is particularly useful at night when it is unlikely that the vehicle interior will be emitting significant amounts of energy in this range.
In the LWIR range (7-15 Microns), people are even more clearly seen against a dark background that is cooler then the person. Finally, millimeter wave radar can be used for occupant sensing as discussed elsewhere. It is important to note that an occupant sensing system can use radiation in more than one of these ranges depending on what is appropriate for the situation. For example, when the sun is bright, then visual imaging can be very effective and when the sun has set, various ranges of infrared become useful. Thus, an occupant sensing system can be a combination of these subsystems. Once again, there is not believed to be any prior art on the use of these imaging techniques for occupant sensing other than that of the current assignee.
8. Field Sensors
Electric and magnetic phenomena can be employed in other ways to sense the presence of an occupant and in particular the fields themselves can be used to determine the dielectric properties, such as the loss tangent or dielectric constant, of occupying items in the passenger compartment. However, it is difficult if not possible to measure these properties using static fields and thus a varying field is used which once again causes electromagnetic waves. Thus, the use of quasi-static low-frequency fields is really a limiting case of the use of waves as described in detail above. Electromagnetic waves are significantly affected at low frequencies, for example, by the dielectric properties of the material. Such capacitive or electric field sensors, for example are described in U.S. patents by Kithil et al. U.S. Pat. No. 5,366,241, U.S. Pat. No. 5,602,734, U.S. Pat. No. 5,691,693, U.S. Pat. No. 5,802,479, U.S. Pat. No. 5,844,486 and U.S. Pat. No. 6,014,602; by Jinno et al. U.S. Pat. No. 5,948,031; by Saito U.S. Pat. No. 6,325,413; by Kleinberg et al. U.S. Pat. No. 0,770,997; and SAE technical papers 982292 and 971051.
Additionally, as discussed in more detail below, the sensing of the change in the characteristics of the near field that surrounds an antenna is an effective and economical method of determining the presence of water or a water-containing life form in the vicinity of the antenna and thus a measure of occupant presence. Measurement of the near field parameters can also yield a specific pattern of an occupant and thus provide a possibility to discriminate a human being from other objects. The use of electric field and capacitance sensors and their equivalence to the occupant sensors described herein requires a special discussion.
Electric and magnetic field sensors and wave sensors are essentially the same from the point of view of sensing the presence of an occupant in a vehicle. In both cases, a time varying electric and/or magnetic field is disturbed or modified by the presence of the occupant. At high frequencies in the visual, infrared and high frequency radio wave region, the sensor is usually based on the reflection of electromagnetic energy. As the frequency drops and more of the energy passes through the occupant, the absorption of the wave energy is measured and at still lower frequencies, the occupant's dielectric properties modify the time varying field produced in the occupied space by the plates of a capacitor. In this latter case, the sensor senses the change in charge distribution on the capacitor plates by measuring, for example, the current wave magnitude or phase in the electric circuit that drives the capacitor.
In all cases, the presence of the occupant reflects, absorbs or modifies the waves or variations in the electric or magnetic fields in the space occupied by the occupant. Thus, for the purposes of this invention, capacitance and inductance, electric field and magnetic field sensors are equivalent and will be considered as wave sensors. What follows is a discussion comparing the similarities and differences between two types of wave sensors, electromagnetic beam sensors and capacitive sensors as exemplified by Kithil in U.S. Pat. No. 5,602,734.
An electromagnetic field disturbed or emitted by a passenger in the case of an electromagnetic beam sensor, for example, and the electric field sensor of Kithil, for example, are in many ways similar and equivalent for the purposes of this invention. The electromagnetic beam sensor is an actual electromagnetic wave sensor by definition, which exploits for sensing a coupled pair of continuously changing electric and magnetic fields, an electromagnetic wave affected or generated by a passenger. The electric field here is not a static, potential one. It is essentially a dynamic, vortex electric field coupled with a changing magnetic field, that is, an electromagnetic wave. It cannot be produced by a steady distribution of electric charges. It is initially produced by moving electric charges in a transmitter, even if this transmitter is a passenger body for the case of a passive infrared sensor.
In the Kithil sensor, a static electric field is declared as an initial material agent coupling a passenger and a sensor (see column 5, lines 5-7): “The proximity sensors 12 each function by creating an electrostatic field between oscillator input loop 54 and detector output loop 56, which is affected by presence of a person near by, as a result of capacitive coupling, . . . ”. It is a potential, non-vortex electric field. It is not necessarily coupled with any magnetic field. It is the electric field of a capacitor. It can be produced with a steady distribution of electric charges. Thus, it is not an electromagnetic wave by definition but if the sensor is driven by a varying current then it produces a varying electric field in the space between the plates of the capacitor which necessarily and simultaneously originates an electromagnetic wave.
Kithil declares that he uses a static electric field in his capacitance sensor. Thus, from the consideration above, one can conclude that Kithil's sensor cannot be treated as a wave sensor because there are no actual electromagnetic waves but only a static electric field of the capacitor in the sensor system. However, this is not the case. The Kithil system could not operate with a true static electric field because a steady system does not carry any information. Therefore, Kithil is forced to use an oscillator, causing an alternating current in the capacitor and a time varying electric field wave in the space between the capacitor plates, and a detector to reveal an informative change of the sensor capacitance caused by the presence of an occupant (see FIG. 7 and its description). In this case, his system becomes a wave sensor in the sense that it starts generating actual electromagnetic waves according to the definition above. That is, Kithil's sensor can be treated as a wave sensor regardless of the degree to which the electromagnetic field that it creates has developed, a beam or a spread shape.
As described in the Kithil patents, the capacitor sensor is a parametric system where the capacitance of the sensor is controlled by influence of the passenger body. This influence is transferred by means of the varying electromagnetic field (i.e., the material agent necessarily originating the wave process) coupling the capacitor electrodes and the body. It is important to note that the same influence takes also place with a true static electric field caused by an unmovable charge distribution, that is in the absence of any wave phenomenon. This would be a situation if there were no oscillator in Kithil's system. However, such a system is not workable and thus Kithil reverts to a dynamic system using electromagnetic waves.
Thus, although Kithil declares the coupling is due to a static electric field, such a situation is not realized in his system because an alternating electromagnetic field (“wave”) exists in the system due to the oscillator. Thus, his sensor is actually a wave sensor, that is, it is sensitive to a change of a wave field in the vehicle compartment. This change is measured by measuring the change of its capacitance. The capacitance of the sensor system is determined by the configuration of its electrodes, one of which is a human body, that is, the passenger inside of and the part which controls the electrode configuration and hence a sensor parameter, the capacitance.
The physics definition of “wave” from Webster's Encyclopedic Unabridged Dictionary is “11. Physics. A progressive disturbance propagated from point to point in a medium or space without progress or advance of the points themselves, . . . ”. In a capacitor, the time that it takes for the disturbance (a change in voltage) to propagate through space, the dielectric and to the opposite plate is generally small and neglected but it is not zero. In space, this velocity of propagation is the speed of light. As the frequency driving the capacitor increases and the distance separating the plates increases, this transmission time as a percentage of the period of oscillation can become significant. Nevertheless, an observer between the plates will see the rise and fall of the electric field much like a person standing in the water of an ocean. The presence of a dielectric body between the plates causes the waves to get bigger as more electrons flow to and from the plates of the capacitor. Thus, an occupant effects the magnitude of these waves which is sensed by the capacitor circuit. Thus, the electromagnetic field is a material agent that carries information about a passenger's position in both Kithil's and a beam type electromagnetic wave sensor.
The following definitions are from the Encyclopedia Britannica:
“electromagnetic field”
“A property of space caused by the motion of an electric charge. A stationary charge will produce only an electric field in the surrounding space. If the charge is moving, a magnetic field is also produced. An electric field can be produced also by a changing magnetic field. The mutual interaction of electric and magnetic fields produces an electromagnetic field, which is considered as having its own existence in space apart from the charges or currents (a stream of moving charges) with which it may be related . . . .” (Copyright 1994-1998 Encyclopedia Britannica).
“displacement current”
“ . . . in electromagnetism, a phenomenon analogous to an ordinary electric current, posited to explain magnetic fields that are produced by changing electric fields. Ordinary electric currents, called conduction currents, whether steady or varying, produce an accompanying magnetic field in the vicinity of the current. [ . . . ]
“As electric charges do not flow through the insulation from one plate of a capacitor to the other, there is no conduction current; instead, a displacement current is said to be present to account for the continuity of the magnetic effects. In fact, the calculated size of the displacement current between the plates of a capacitor being charged and discharged in an alternating-current circuit is equal to the size of the conduction current in the wires leading to and from the capacitor. Displacement currents play a central role in the propagation of electromagnetic radiation, such as light and radio waves, through empty space. A traveling, varying magnetic field is everywhere associated with a periodically changing electric field that may be conceived in terms of a displacement current. Maxwell's insight on displacement current, therefore, made it possible to understand electromagnetic waves as being propagated through space completely detached from electric currents in conductors.” Copyright 1994-1998 Encyclopedia Britannica.
“electromagnetic radiation”
“ . . . energy that is propagated through free space or through a material medium in the form of electromagnetic waves, such as radio waves, visible light, and gamma rays. The term also refers to the emission and transmission of such radiant energy. [ . . . ]
“It has been established that time-varying electric fields can induce magnetic fields and that time-varying magnetic fields can in like manner induce electric fields. Because such electric and magnetic fields generate each other, they occur jointly, and together they propagate as electromagnetic waves. An electromagnetic wave is a transverse wave in that the electric field and the magnetic field at any point and time in the wave are perpendicular to each other as well as to the direction of propagation. [ . . . ]
“Electromagnetic radiation has properties in common with other forms of waves such as reflection, refraction, diffraction, and interference. [ . . . ]” Copyright 1994-1998 Encyclopedia Britannica
The main part of the Kithil “circuit means” is an oscillator, which is as necessary in the system as the capacitor itself to make the capacitive coupling effect be detectable. An oscillator by nature creates waves, The system can operate as a sensor only if an alternating current flows through the sensor capacitor, which, in fact, is a detector from which an informative signal is acquired. Then this current (or, more exactly, integral of the current over time-charge) is measured and the result is a measure of the sensor capacitance value. The latter in turn depends on the passenger presence that affects the magnitude of the waves that travel between the plates of the capacitor making the Kithil sensor a wave sensor by the definition herein.
An additional relevant definition is:
(Telecom Glossary, atis.org/tg2k/ capacitive coupling.html)
“capacitive coupling: The transfer of energy from one circuit to another by means of the mutual capacitance between the circuits. (188) Note 1: The coupling may be deliberate or inadvertent. Note 2: Capacitive coupling favors transfer of the higher frequency components of a signal, whereas inductive coupling favors lower frequency components, and conductive coupling favors neither higher nor lower frequency components.”
Another similarity between one embodiment of the sensor of this invention and the Kithil sensor is the use of a voltage-controlled oscillator (VCO).
9. Telematics
One key invention disclosed here and in the current assignee's above-referenced patents is that once an occupancy has been categorized one of the many ways that the information can be used is to transmit all or some of it to a remote location via a telematics link. This link can be a cell phone, WiFi Internet connection or a satellite (LEO or geo-stationary). The recipient of the information can be a governmental authority, a company or an EMS organization.
For example, vehicles can be provided with a standard cellular phone as well as the Global Positioning System (GPS), an automobile navigation or location system with an optional connection to a manned assistance facility, which is now available on a number of vehicle models. In the event of an accident, the phone may automatically call 911 for emergency assistance and report the exact position of the vehicle. If the vehicle also has a system as described herein for monitoring each seat location, the number and perhaps the condition of the occupants could also be reported. In that way, the emergency service (EMS) would know what equipment and how many ambulances to send to the accident site. Moreover, a communication channel can be opened between the vehicle and a monitoring facility/emergency response facility or personnel to enable directions to be provided to the occupant(s) of the vehicle to assist in any necessary first aid prior to arrival of the emergency assistance personnel.
One existing service is OnStar® provided by General Motors that automatically notifies an OnStar® operator in the event that the airbags deploy. By adding the teachings of the inventions herein, the service can also provide a description on the number and category of occupants, their condition and the output of other relevant information including a picture of a particular seat before and after the accident if desired. There is not believed to be any prior art for these added services.
10. Display Heads-up displays are normally projected onto the windshield. In a few cases, they can appear on a visor that is placed in front of the driver or vehicle passenger. Here, the use of the term heads-up display or HUD will be meant to encompass both systems.
10.1 Heads-up Display (HUD)
Various manufacturers have attempted to provide information to a driver through the use of a heads-up display. In some cases, the display is limited to information that would otherwise appear on the instrument panel. In more sophisticated cases, there is an attempt to display information about the environment that would be useful to the driver. Night vision cameras can record that there is a person or an object ahead on the road that the vehicle might run into if the driver is not aware of its presence. Present day systems of this type provide a display at the bottom of the windshield of the scene sensed by the night vision camera. No attempt is made to superimpose this onto the windshield such that the driver would see it at the location that he would normally see it if the object were illuminated. This confuses the driver and in one study the driver actually performed worse than he would have in the absence of the night vision information.
The ability to find the eyes of the driver, as taught here, permits the placement of the night vision image exactly where the driver expects to see it. An enhancement is to categorize and identify the objects that should be brought to the attention of the driver and then place an icon at the proper place in the driver's field of view. There is no known prior art of these inventions. There is of course much prior art on night vision. See for example, M. Aguilar, D. A. Fay, W. D. Ross, A. M. Waxman, D. B. Ireland, J. P. Racamato, “Real-time fusion of low-light CCD and uncooled IR imagery for color night vision”, SPIE Vol. 3364 (1998).
The University of Minnesota attempts to show the driver of a snow plow where the snow covered road edges are on a LCD display that is placed in front of the windshield. Needless to say this also can confuse the driver and a preferable approach, as disclosed herein, is to place the edge markings on the windshield as they would appear if the driver could see the road. This again requires knowledge of the location of the eyes of the driver.
Many other applications of display technology come to mind including aids to a lost driver from the route guidance system. An arrow, lane markings or even a pseudo-colored lane can be properly placed in his field of view when he should make a turn, for example or direct the driver to the closest McDonalds or gas station. For the passenger, objects of interest along with short descriptions (written or oral) can be highlighted on the HUD if the locations of the eyes of the passenger are known. In fact, all of the windows of the vehicle can become semi-transparent computer screens and be used as a virtual reality or augmented reality system guiding the driver and providing information about the environment that is generated by accurate maps, sensors and inter-vehicle communication and vehicle to infrastructure communication. This becomes easier with the development of organic displays that comprise a thin film that can be manufactured as part of the window or appear as part of a transparent visor. Again there is not believed to be any prior art on these features.
10.2 Adjust HUD Based on Driver Seating Position
A simpler system that can be implemented without an occupant sensor is to base the location of the HUD display on the expected location of the eyes of the driver that can be calculated from other sensor information such as the position of the rear view mirror, seat and weight of the occupant. Once an approximate location for the display is determined, a knob of another system can be provided to permit the driver to fine tune that location. Again there is not believed to be any prior art for this concept. Some relevant patents are U.S. Pat. No. 5,668,907 and WO0235276.
10.3 HUD on Rear Window
In some cases, it might be desirable to project the HUD onto the rear window or in some cases even the side windows. For the rear window, the position of the mirror and the occupant's eyes would be useful in determining where to place the image. The position of the eyes of the driver or passenger again would be useful for a HUD display on the side windows. Finally, for an entertainment system, the positions of the eyes of a passenger can allow the display of three-dimensional images onto any in-vehicle display. See for example U.S. Pat. No. 6,291,906.
10.4 Plastic Electronics
Heads-up displays heretofore have been based on projection systems. With the development of plastic electronics, the possibility now exists for elimination of the projection system and to create the image directly on the windshield. Relevant patents for this technology include U.S. Pat. No. 5,661,553, U.S. Pat. No. 5,796,454, U.S. Pat. No. 5,889,566, and U.S. Pat. No. 5,933,203. A relevant paper is “Polymer Material Promises an Inexpensive and Thin Full-Color Light-Emitting Plastic Display”, Electronic Design Magazine, Jan. 9, 1996. This display material can be used in conjunction with SPD, for example, to turn the vehicle windows into a multicolored display. Also see “Bright Future for Displays”, MIT Technology Review, pp 82-3, April, 2001.
11. Pattern Recognition
Many of the teachings of the inventions herein are based on pattern recognition technologies as taught in numerous textbooks and technical papers. For example, an important part of the diagnostic teachings of this invention are the manner in which the diagnostic module determines a normal pattern from an abnormal pattern and the manner in which it decides what data to use from the vast amount of data available. This is accomplished using pattern recognition technologies, such as artificial neural networks, combination neural networks, support vector machines, cellular neural networks etc.
The present invention relating to occupant sensing uses sophisticated pattern recognition capabilities such as fuzzy logic systems, neural networks, neural-fuzzy systems or other pattern recognition computer-based algorithms to the occupant position measurement system disclosed in the above referenced patents and/or patent applications and greatly extends the areas of application of this technology.
The pattern recognition techniques used can be applied to the preprocessed data acquired by various transducers or to the raw data itself depending on the application. For example, as reported in the current assignee's patent applications above-referenced, there is frequently information in the frequencies present in the data and thus a Fourier transform of the data can be inputted into the pattern recognition algorithm. In optical correlation methods, for example, a very fast identification of an object can be obtained using the frequency domain rather than the time domain. Similarly, when analyzing the output of weight sensors the transient response is usually more accurate that the static response, as taught in the current assignee's patents and applications, and this transient response can be analyzed in the frequency domain or in the time domain. An example of the use of a simple frequency analysis is presented in U.S. Pat. No. 6,005,485 to Kursawe.
11.1 Neural Nets
The theory of neural networks including many examples can be found in several books on the subject including: (1) Techniques and Application of Neural Networks, edited by Taylor, M. and Lisboa, P., Ellis Horwood, West Sussex, England, 1993; (2) Naturally Intelligent Systems, by Caudill, M. and Butler, C., MIT Press, Cambridge Mass., 1990; (3) J. M. Zaruda, Introduction to Artificial Neural Systems, West publishing Co., N.Y., 1992, (4) Digital Neural Networks, by Kung, S. Y., PTR Prentice Hall, Englewood Cliffs, N.J., 1993, Eberhart, R., Simpson, P., (5) Dobbins, R., Computational Intelligence PC Tools, Academic Press, Inc., 1996, Orlando, Fla., (6) Cristianini, N. and Shawe-Taylor, J. An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Cambridge University Press, Cambridge England, 2000; (7) Proceedings of the 2000 6th IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA 2000), IEEE, Piscataway N.J.; and (8) Sinha, N. K. and Gupta, M.M. Soft Computing & Intelligent Systems, Academic Press 2000 San Diego, Calif. The neural network pattern recognition technology is one of the most developed of pattern recognition technologies. The invention described herein uses combinations of neural networks to improve the pattern recognition process.
An example of such a pattern recognition system using neural networks using sonar is discussed in two papers by Gorman, R. P. and Sejnowski, T. J. “Analysis of Hidden Units in a Layered Network Trained to Classify Sonar Targets”, Neural Networks, Vol. 1. pp. 75-89, 1988, and “Learned Classification of Sonar Targets Using a Massively Parallel Network”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 36, No. 7, July 1988. A more recent example using cellular neural networks is: M. Milanove, U. Büker, “Object recognition in image sequences with cellular neural networks”, Neurocomputing 31 (2000) 124-141, Elsevier. Another recent example using support vector machines, a form of neural network, is: E. Destéfanis, E. Kienzle, L. Canali, “Occupant Detection Using Support Vector Machines With a Polynomial Kernel Function”, SPIE Vol. 4192 (2000).
Japanese Patent No. 3-42337 (A) to Ueno describes a device for detecting the driving condition of a vehicle driver comprising a light emitter for irradiating the face of the driver and a means for picking up the image of the driver and storing it for later analysis. Means are provided for locating the eyes of the driver and then the irises of the eyes and then determining if the driver is looking to the side or sleeping. Ueno determines the state of the eyes of the occupant rather than determining the location of the eyes relative to the other parts of the vehicle passenger compartment. Such a system can be defeated if the driver is wearing glasses, particularly sunglasses, or another optical device which obstructs a clear view of his/her eyes. Pattern recognition technologies such as neural networks are not used. The method of finding the eyes is described but not a method of adapting the system to a particular vehicle model.
U.S. Pat. No. 5,008,946 to Ando uses a complicated set of rules to isolate the eyes and mouth of a driver and uses this information to permit the driver to control the radio, for example, or other systems within the vehicle by moving his eyes and/or mouth. Ando uses visible light and illuminates only the head of the driver. He also makes no use of trainable pattern recognition systems such as neural networks, nor is there any attempt to identify the contents neither of the vehicle nor of their location relative to the vehicle passenger compartment. Rather, Ando is limited to control of vehicle devices by responding to motion of the driver's mouth and eyes. As with Ueno, a method of finding the eyes is described but not a method of adapting the system to a particular vehicle model.
U.S. Pat. No. 5,298,732 and U.S. Pat. No. 5,714,751 to Chen also concentrate on locating the eyes of the driver so as to position a light filter in the form of a continuously repositioning small sun visor or liquid crystal shade between a light source such as the sun or the lights of an oncoming vehicle, and the driver's eyes. Chen does not explain in detail how the eyes are located but does supply a calibration system whereby the driver can adjust the filter so that it is at the proper position relative to his or her eyes. Chen references the use of automatic equipment for determining the location of the eyes but does not describe how this equipment works. In any event, in Chen, there is no mention of illumination of the occupant, monitoring the position of the occupant, other than the eyes, determining the position of the eyes relative to the passenger compartment, or identifying any other object in the vehicle other than the driver's eyes. Also, there is no mention of the use of a trainable pattern recognition system. A method for finding the eyes is described but not a method of adapting the system to a particular vehicle model.
U.S. Pat. No. 5,305,012 to Faris also describes a system for reducing the glare from the headlights of an oncoming vehicle. Faris locates the eyes of the occupant by using two spaced apart infrared cameras using passive infrared radiation from the eyes of the driver. Again, Faris is only interested in locating the driver's eyes relative to the sun or oncoming headlights and does not identify or monitor the occupant or locate the occupant, a rear facing child seat or any other object for that matter, relative to the passenger compartment or the airbag. Also, Faris does not use trainable pattern recognition techniques such as neural networks. Faris, in fact, does not even say how the eyes of the occupant are located but refers the reader to a book entitled Robot Vision (1991) by Berthold Horn, published by MIT Press, Cambridge, Mass. A review of this book did not appear to provide the answer to this question. Also, Faris uses the passive infrared radiation rather than illuminating the occupant with ultrasonic or electromagnetic radiation as in some implementations of the instant invention. A method for finding the eyes of the occupant is described but not a method of adapting the system to a particular vehicle model.
The use of neural networks, or neural fuzzy systems, and in particular combination neural networks, as the pattern recognition technology and the methods of adapting this to a particular vehicle, such as the training methods, is important to some of the inventions herein since it makes the monitoring system robust, reliable and accurate. The resulting algorithm created by the neural network program is usually short with a limited number of lines of code written in the C or C++ computer language as opposed to typically a very large algorithm when the techniques of the above patents to Ando, Chen and Faris are implemented. As a result, the resulting systems are easy to implement at a low cost, making them practical for automotive applications. The cost of the ultrasonic transducers, for example, is expected to be less than about $1 in quantities of one million per year and of the CCD and CMOS arrays, which have been prohibitively expensive until recently, currently are estimated to cost less than $5 each in similar quantities also rendering their use practical. Similarly, the implementation of the techniques of the above referenced patents requires expensive microprocessors while the implementation with neural networks and similar trainable pattern recognition technologies permits the use of low cost microprocessors typically costing less than $10 in large quantities.
The present invention is best implemented using sophisticated software that develops trainable pattern recognition algorithms such as neural networks and combination neural networks. Usually, the data is preprocessed, as discussed below, using various feature extraction techniques and the results post-processed to improve system accuracy. Examples of feature extraction techniques can be found in U.S. Pat. No. 4,906,940 entitled “Process and Apparatus for the Automatic Detection and Extraction of Features in Images and Displays” to Green et al. Examples of other more advanced and efficient pattern recognition techniques can be found in U.S. Pat. No. 5,390,136 entitled “Artificial Neuron and Method of Using Same” and U.S. Pat. No. 5,517,667 entitled “Neural Network That Does Not Require Repetitive Training” to S. T. Wang. Other examples include U.S. Pat. No. 5,235,339 (Morrison et al.), U.S. Pat. No. 5,214,744 (Schweizer et al), U.S. Pat. No. 5,181,254 (Schweizer et al), and U.S. Pat. No. 4,881,270 (Knecht et al). Neural networks as used herein include all types of neural networks including modular neural networks, cellular neural networks and support vector machines and all combinations as described in detail in U.S. Pat. No. 6,445,988 and referred to therein as “combination neural networks”
11.2 Combination Neural Nets
A “combination neural network” as used herein will generally apply to any combination of two or more neural networks that are either connected together or that analyze all or a portion of the input data. A combination neural network can be used to divide up tasks in solving a particular occupant problem. For example, one neural network can be used to identify an object occupying a passenger compartment of an automobile and a second neural network can be used to determine the position of the object or its location with respect to the airbag, for example, within the passenger compartment. In another case, one neural network can be used merely to determine whether the data is similar to data upon which a main neural network has been trained or whether there is something radically different about this data and therefore that the data should not be analyzed. Combination neural networks can sometimes be implemented as cellular neural networks.
Consider a comparative analysis performed by neural networks to that performed by the human mind. Once the human mind has identified that the object observed is a tree, the mind does not try to determine whether it is a black bear or a grizzly. Further observation on the tree might center on whether it is a pine tree, an oak tree etc.
Thus, the human mind appears to operate in some manner like a hierarchy of neural networks. Similarly, neural networks for analyzing the occupancy of the vehicle can be structured such that higher order networks are used to determine, for example, whether there is an occupying item of any kind present. Another neural network could follow, knowing that there is information on the item, with attempts to categorize the item into child seats and human adults etc., i.e., determine the type of item.
Once it has decided that a child seat is present, then another neural network can be used to determine whether the child seat is rear facing or forward facing. Once the decision has been made that the child seat is facing rearward, the position of the child seat relative to the airbag, for example, can be handled by still another neural network. The overall accuracy of the system can be substantially improved by breaking the pattern recognition process down into a larger number of smaller pattern recognition problems. Naturally, combination neural networks can now be applied to solving many other pattern recognition problems in and outside of a vehicle including vehicle diagnostics, collision avoidance, anticipatory sensing etc.
In some cases, the accuracy of the pattern recognition process can be improved if the system uses data from its own recent decisions. Thus, for example, if the neural network system had determined that a forward facing adult was present, then that information can be used as input into another neural network, biasing any results toward the forward facing human compared to a rear facing child seat, for example. Similarly, for the case when an occupant is being tracked in his or her forward motion during a crash, for example, the location of the occupant at the previous calculation time step can be valuable information to determining the location of the occupant from the current data. There is a limited distance an occupant can move in 10 milliseconds, for example. In this latter example, feedback of the decision of the neural network tracking algorithm becomes important input into the same algorithm for the calculation of the position of the occupant at the next time step.
What has been described above is generally referred to as modular neural networks with and without feedback. Actually, the feedback does not have to be from the output to the input of the same neural network. The feedback from a downstream neural network could be input to an upstream neural network, for example.
The neural networks can be combined in other ways, for example in a voting situation. Sometimes the data upon which the system is trained is sufficiently complex or imprecise that different views of the data will give different results. For example, a subset of transducers may be used to train one neural network and another subset to train a second neural network etc. The decision can then be based on a voting of the parallel neural networks, sometimes known as an ensemble neural network. In the past, neural networks have usually only been used in the form of a single neural network algorithm for identifying the occupancy state of an automobile. This invention is primarily advancing the state of the art and using combination neural networks wherein two or more neural networks are combined to arrive at a decision.
The applications for this technology are numerous as described in the patents and patent applications listed above. However, the main focus of some of the instant inventions is the process and resulting apparatus of adapting the system in the patents and patent applications referenced above and using combination neural networks for the detection of the presence of an occupied child seat in the rear facing position or an out-of-position occupant and the detection of an occupant in a normal seating position. The system is designed so that in the former two cases, deployment of the occupant protection apparatus (airbag) may be controlled and possibly suppressed, and in the latter case, it will be controlled and enabled.
One preferred implementation of a first generation occupant sensing system, which is adapted to various vehicle models using the teachings presented herein, is an ultrasonic occupant position sensor, as described below and in the current assignee's above-referenced patents. This system uses a Combination Artificial Neural Network (CANN) to recognize patterns that it has been trained to identify as either airbag enable or airbag disable conditions. The pattern can be obtained from four ultrasonic transducers that cover the front passenger seating area. This pattern consists of the ultrasonic echoes bouncing off of the objects in the passenger seat area. The signal from each of the four transducers includes the electrical representation of the return echoes, which is processed by the electronics. The electronic processing can comprise amplification, logarithmic compression, rectification, and demodulation (band pass filtering), followed by discretization (sampling) and digitization of the signal. The only software processing required, before this signal can be fed into the combination artificial neural network, is normalization (i.e., mapping the input to a fixed range such as numbers between 0 and 1). Although this is a fair amount of processing, the resulting signal is still considered “raw”, because all information is treated equally.
A further important application of CANN is where optical sensors such as cameras are used to monitor the inside or outside of a vehicle in the presence of varying illumination conditions. At night, artificial illumination usually in the form of infrared radiation is frequently added to the scene. For example, when monitoring the interior of a vehicle one or more infrared LEDs are frequently used to illuminate the occupant and a pattern recognition system is trained under such lighting conditions. In bright daylight, however, unless the infrared illumination is either very bright or in the form of a scanning laser with a narrow beam, the sun can overwhelm the infrared. However, in daylight there is no need for artificial illumination but the patterns of reflected radiation differ significantly from the infrared case. Thus, a separate pattern recognition algorithm is frequently trained to handle this case. Furthermore, depending on the lighting conditions, more than two algorithms can be trained to handle different cases. If CANN is used for this case, the initial algorithm can determine the category of illumination that is present and direct further processing to a particular neural network that has been trained under similar conditions. Another example would be the monitoring of objects in the vicinity of the vehicle. There is no known prior art on the use on neural networks, pattern recognition algorithms or, in particular, CANN for systems that monitor either the interior or the exterior of a vehicle.
11.3 Interpretation of Other Occupant States—Inattention, Sleep
Another example of an invention herein involves the monitoring of the driver's behavior over time that can be used to warn a driver if he or she is falling asleep, or to stop the vehicle if the driver loses the capacity to control it.
A paper entitled “Intelligent System for Video Monitoring of Vehicle Cockpit” by S. Boverie et al., SAE Technical Paper Series No. 980613, Feb. 23-26, 1998, describes the installation of an optical/retina sensor in the vehicle and several uses of this sensor. Possible uses are said to include observation of the driver's face (eyelid movement) and the driver's attitude to allow analysis of the driver's vigilance level and warn him/her about critical situations and observation of the front passenger seat to allow the determination of the presence of somebody or something located on the seat and to value the volumetric occupancy of the passenger for the purpose of optimizing the operating conditions for airbags.
11.4 Combining Occupant Monitoring and Car Monitoring
As discussed above and in the assignee's above-referenced patents and in particular in U.S. Pat. No. 6,532,408, the vehicle and the occupant can be simultaneously monitored in order to optimize the deployment of the restraint system, for example, using pattern recognition techniques such as CANN. Similarly, the position of the head of an occupant can be monitored while at the same time the likelihood of a side impact or a rollover can be monitored by a variety of other sensor systems such as an IMU, gyroscopes, radar, laser radar, ultrasound, cameras etc. and deployment of the side curtain airbag initiated if the occupant's head is getting too close to the side window. There are of course many other examples where the simultaneous monitoring of two environments can be combined, preferably using pattern recognition, to cause an action that would not be warranted by an analysis of only one environment. There is no known prior art except the current assignee's of monitoring more than one environment to render a decision that would not have been made based on the monitoring of a single environment and particularly through the use of pattern recognition, trained pattern recognition, neural networks or combination neural networks in the automotive field.
CANN, as well as the other pattern recognition systems discussed herein, can be implemented in either software or in hardware through the use of cellular neural networks, support vector machines, ASIC, systems on a chip, or FPGAs depending on the particular application and the quantity of units to be made. In particular, for many applications where the volume is large but not huge, a rapid and relatively low cost implementation could be to use a field programmable gate array (FPGA). This technology lends itself well to the implementation of multiple connected networks such as some implementations of CANN.
11.5 Continuous Tracking
During the process of adapting an occupant monitoring system to a vehicle, for example, the actual position of the occupant can be an important input during the training phase of a trainable pattern recognition system. Thus, for example, it might be desirable to associate a particular pattern of data from one or more cameras to the measured location of the occupant relative to the airbag. Thus, it is frequently desirable to positively measure the location of the occupant with another system while data collection is taking place. Systems for performing this measurement function include string potentiometers attached to the head or chest of the occupant, for example, inertial sensors such as an IMU attached to the occupant, laser optical systems using any part of the spectrum such as the far, mid or near infrared, visible and ultraviolet, radar, laser radar, stereo or focusing cameras, RF emitters attached to the occupant, or any other such measurement system. There is no known prior art for continuous tracking systems to be used in data collection when adapting a system for monitoring the interior or exterior of a vehicle.
11.6 Preprocessing
There are many preprocessing techniques that are and can be used to prepare the data for input into a pattern recognition or other analysis system in an interior or exterior monitoring system. The simplest systems involve subtracting one image from another to determine motion of the object of interest and to subtract out the unchanging background, removing some data that is known not to contain any useful information such as the early and late portions of an ultrasonic reflected signal, scaling, smoothing of filtering the data etc. More sophisticated preprocessing algorithms involve applying a Fourier transform, combining data from several sources using “sensor fusion” techniques, finding edges of objects and their orientation and elimination of non-edge data, finding areas having the same color or pattern and identifying such areas, image segmentation and many others. Very little preprocessing prior art exists other than that of the current assignee. The prior art is limited to the preprocessing techniques of Ando, Chen and Faris for eye detection and the sensor fusion techniques of Corrado all discussed above.
11.7 Post Processing
In some cases, after the system has made a decision that there is an out-of-position adult occupying the passenger seat, for example, it is useful for compare that decision with another recent decision to see it they are consistent. If the previous decision 10 milliseconds ago indicates that the adult was safely in position then thermal gradients or some other anomaly perhaps corrupted the data and thus the decision and the new decision should be ignored unless subsequently confirmed. Post processing can involve a number of techniques including averaging the decisions with a 5 decision moving average, applying other more sophisticated filters, applying limits to the decision or to the change from the previous decision, comparing data point by data point the input data that lead to the changed decision and correcting data points that appear to be in error etc. A goal of post processing is to apply a reasonableness test to the decision and thus to improve the accuracy of the decision or eliminate erroneous decisions. There appears to be no known prior art for post processing in the automotive monitoring field other than that of the current assignee.
12. Optical Correlators
Optical methods for data correlation analysis are utilized in systems for military purpose such as target tracking, missile self-guidance, aerospace reconnaissance data processing etc. Advantages of these methods are the possibility of parallel processing of the elements of images being recognized providing high speed recognition and the ability to use advanced optical processors created by means of integrated optics technologies.
Some prior art includes the following technical papers:                1. I. Mirkin, L. Singher “Adaptive Scale Invariant Filters”, SPIE Vol. 3159, 1997        2. B. Javidi “Non-linear Joint Transform Correlators”, University of Conn.        3. A. Awwal, H. Michel “Single Step Joint Fourier Transform Correlator”, SPIE Vol. 3073, 1997        4. M. O'Callaghan, D. Ward, S. Perlmuter, L. Ji, C. Walker “A highly integrated single-chip optical correlator” SPIE Vol. 3466, 1998        
These papers describe the use of optical methods and tools (optical correlators and spectral analyzers) for image recognition. Paper [1] discusses the use of an optical correlation technique for transforming an initial image to a form invariant to displacements of the respective object in the view. The very recognition of the object is done using a sectoring mask that is built by training with a genetic algorithm similar to methods of neural network training. The system discussed in the paper [2] includes an optical correlator that performs projection of the spectra of the target and the sample images onto a CCD matrix which functions as a detector. The consistent spectrum image at its output is used to detect the maximum of the correlation function by the median filtration method. Papers [3], [4] discuss some designs of optical correlators.
The following should be noted in connection with the discussion on the use of optical correlators for a vehicle compartment occupant position sensing task:                1) Making use of optical correlators to detect and classify objects in presence of noise is efficient when the amount of possible alternatives of the object's shape and position is comparatively small with respect to the number of elements in the scene. This is apparent from the character of demonstration samples in papers [1], [2] where there were only a few sample scenes and their respective scale factors involved.        2) The effectiveness of making use of optical correlation methods in systems of military purpose can be explained by a comparatively small number of classes of military objects to be recognized and a low probability of catching several objects of this kind with a single view.        3) In their principles of operation and capabilities, optical correlators are similar to neural associative memory.        
In the task of occupant's position sensing in a car compartment, for example, the description of the sample object is represented by a training set that can include hundreds of thousands of various images. This situation is fundamentally different from those discussed in the mentioned papers. Therefore, the direct use of the optical correlation methods appears to be difficult and expensive.
Nevertheless, making use of the correlation centering technique in order to reduce the image description's redundancy can be a valuable technique. This task could involve a contour extraction technique that does not require excessive computational effort but may have limited capabilities as to the reduction of redundancy. The correlation centering can demand significantly more computational resources, but the spectra obtained in this way will be invariant to objects' displacements and, possibly, will maintain the classification features needed by the neural network for the purpose of recognition.
Once again, no prior art is believed to exist on the application of optical correlation techniques to the monitoring of either the interior or the exterior of the vehicle other than that of the current assignee.
13. Other Inputs
Many other inputs can be applied to the interior or exterior monitoring systems of the inventions disclosed herein. For interior monitoring these can include, among others, the position of the seat and seatback, vehicle velocity, brake pressure, steering wheel position and motion, exterior temperature and humidity, seat weight sensors, accelerometers and gyroscopes, engine behavior sensors, tire monitors and chemical (oxygen carbon dioxide, alcohol, etc.) sensors. For external monitoring these can include, among others, temperature and humidity, weather forecasting information, traffic information, hazard warnings, speed limit information, time of day, lighting and visibility conditions and road condition information.
14. Other Products, Outputs, Features
Pattern recognition technology is important to the development of smart airbags that the occupant identification and position determination systems described in the above-referenced patents and patent applications and to the methods described herein for adapting those systems to a particular vehicle model and for solving particular subsystem problems discussed in this section. To complete the development of smart airbags, an anticipatory crash detecting system such as disclosed in U.S. Pat. No. 6,343,810 is also desirable. Prior to the implementation of anticipatory crash sensing, the use of a neural network smart crash sensor, which identifies the type of crash and thus its severity based on the early part of the crash acceleration signature, should be developed and thereafter implemented.
U.S. Pat. No. 5,684,701 describes a crash sensor based on neural networks. This crash sensor, as with all other crash sensors, determines whether or not the crash is of sufficient severity to require deployment of the airbag and, if so, initiates the deployment. A smart airbag crash sensor based on neural networks can also be designed to identify the crash and categorize it with regard to severity thus permitting the airbag deployment to be matched not only to the characteristics and position of the occupant but also the severity and timing of the crash itself as described in more detail in U.S. Pat. No. 5,943,295.
The applications for this technology are numerous as described in the current assignee's patents and patent applications listed herein. They include, among others: (i) the monitoring of the occupant for safety purposes to prevent airbag deployment induced injuries, (ii) the locating of the eyes of the occupant (driver) to permit automatic adjustment of the rear view mirror(s), (iii) the location of the seat to place the occupant's eyes at the proper position to eliminate the parallax in a heads-up display in night vision systems, (iv) the location of the ears of the occupant for optimum adjustment of the entertainment system, (v) the identification of the occupant for security or other reasons, (vi) the determination of obstructions in the path of a closing door or window, (vii) the determination of the position of the occupant's shoulder so that the seat belt anchorage point can be adjusted for the best protection of the occupant, (viii) the determination of the position of the rear of the occupants head so that the headrest or other system can be adjusted to minimize whiplash injuries in rear impacts, (ix) anticipatory crash sensing, (x) blind spot detection, (xi) smart headlight dimmers, (xii) sunlight and headlight glare reduction and many others. In fact, over forty products alone have been identified based on the ability to identify and monitor objects and parts thereof in the passenger compartment of an automobile or truck. In addition, there are many other applications of the apparatus and methods described herein for monitoring the environment exterior to the vehicle.
Unless specifically stated otherwise below, there is no known prior art for any of the applications listed in this section.
14.1 Inflator Control
Inflators now exist which will adjust the amount of gas flowing to or from the airbag to account for the size and position of the occupant and for the severity of the accident. The vehicle identification and monitoring system (VIMS) discussed in U.S. Pat. No. 5,829,782, and U.S. Pat. No. 5,943,295 among others, can control such inflators based on the presence and position of vehicle occupants or of a rear facing child seat. Some of the inventions herein are concerned with the process of adapting the vehicle interior monitoring systems to a particular vehicle model and achieving a high system accuracy and reliability as discussed in greater detail below. The automatic adjustment of the deployment rate of the airbag based on occupant identification and position and on crash severity has been termed “smart airbags” and is discussed in great detail in U.S. Pat. No. 6,532,408.
14.2 Seat Adjustment
The adjustment of an automobile seat occupied by a driver of the vehicle is now accomplished by the use of either electrical switches and motors or by mechanical levers. As a result, the driver's seat is rarely placed at the proper driving position which is defined as the seat location which places the eyes of the driver in the so-called “eye ellipse” and permits him or her to comfortably reach the pedals and steering wheel. The “eye ellipse” is the optimum eye position relative to the windshield and rear view mirror of the vehicle.
There are a variety of reasons why the eye ellipse, which is actually an ellipsoid, is rarely achieved by the actions of the driver. One reason is the poor design of most seat adjustment systems particularly the so-called “4-way-seat”. It is known that there are three degrees of freedom of a seat bottom, namely vertical, longitudinal, and rotation about the lateral or pitch axis. The 4-way-seat provides four motions to control the seat: (1) raising or lowering the front of the seat, (2) raising or lowering the back of the seat, (3) raising or lowering the entire seat, (4) moving the seat fore and aft. Such a seat adjustment system causes confusion since there are four control motions for three degrees of freedom. As a result, vehicle occupants are easily frustrated by such events as when the control to raise the seat is exercised, the seat not only is raised but is also rotated. Occupants thus find it difficult to place the seat in the optimum location using this system and frequently give up trying leaving the seat in an improper driving position. This problem could be solved by the addition of a microprocessor and the elimination of one switch.
Many vehicles today are equipped with a lumbar support system that is never used by most occupants. One reason is that the lumbar support cannot be preset since the shape of the lumbar for different occupants differs significantly, for example a tall person has significantly different lumbar support requirements than a short person. Without knowledge of the size of the occupant, the lumbar support cannot be automatically adjusted.
As discussed in the above referenced '320 patent, in approximately 95% of the cases where an occupant suffers a whiplash injury, the headrest is not properly located to protect him or her in a rear impact collision. Thus, many people are needlessly injured. Also, the stiffness and damping characteristics of a seat are fixed and no attempt is made in any production vehicle to adjust the stiffness and damping of the seat in relation to either the size or weight of an occupant or to the environmental conditions such as road roughness. All of these adjustments, if they are to be done automatically, require knowledge of the morphology of the seat occupant. The inventions disclosed herein provide that knowledge. Other than that of the current assignee, there is no known prior art for the automatic adjustment of the seat based on the driver's morphology. U.S. Pat. No. 4,797,824 to Sugiyama uses visible colored light to locate the eyes of the driver with the assistance of the driver. Once the eye position is determined, the headrest and the seat are adjusted for optimum protection.
14.3 Side Impacts
Side impact airbag systems began appearing on 1995 vehicles. The danger of deployment-induced injuries will exist for side impact airbags as they now do for frontal impact airbags. A child with his head against the airbag is such an example. The system of this invention will minimize such injuries. This fact has been also realized subsequent to its disclosure by the current assignee by NEC and such a system now appears on Honda vehicles. There is no other known prior art.
14.4 Children and Animals Left Alone
It is a problem in vehicles that children, infants and pets are sometimes left alone, either intentionally or inadvertently, and the temperature in the vehicle rises or falls. The child, infant or pet is then suffocated by the lack of oxygen in the vehicle or frozen. This problem can be solved by the inventions disclosed herein since the existence of the occupant can be determined as well as the temperature and even oxygen content is desired and preventative measures automatically taken. Similarly, children and pets die every year from suffocation after being locked in a vehicle trunk. The sensing of a life form in the trunk is discussed below.
14.5 Vehicle Theft
Another problem relates to the theft of vehicles. With an interior monitoring system, or a variety of other sensors as disclosed herein, connected with a telematics device, the vehicle owner could be notified if someone attempted to steal the vehicle while the owner was away.
14.6 Security, Intruder Protection
There have been incidents when a thief waits in a vehicle until the driver of the vehicle enters the vehicle and then forces the driver to provide the keys and exit the vehicle. Using the inventions herein, a driver can be made aware that the vehicle is occupied before he or she enters and thus he or she can leave and summon help. Motion of an occupant in the vehicle who does not enter the key into the ignition can also be sensed and the vehicle ignition, for example, can be disabled. In more sophisticated cases, the driver can be identified and operation of the vehicle enabled. This would eliminate the need even for a key.
14.7 Entertainment System Control
Once an occupant sensor is operational, the vehicle entertainment system can be improved if the number, size and location of occupants and other objects are known. However, prior to the inventions disclosed herein engineers have not thought to determine the number, size and/or location of the occupants and use such determination in combination with the entertainment system. Indeed, this information can be provided by the vehicle interior monitoring system disclosed herein to thereby improve a vehicle's entertainment system. Once one considers monitoring the space in the passenger compartment, an alternate method of characterizing the sonic environment comes to mind which is to send and receive a test sound to see what frequencies are reflected, absorbed or excite resonances and then adjust the spectral output of the entertainment system accordingly.
As the internal monitoring system improves to where such things as the exact location of the occupants' ears and eyes can be determined, even more significant improvements to the entertainment system become possible through the use of noise canceling sound. It is even possible to beam sound directly to the ears of an occupant using hypersonic-sound if the ear location is known. This permits different occupants to enjoy different programming at the same time.
14.8 HVAC
Similarly to the entertainment system, the heating, ventilation and air conditioning system (HVAC) could be improved if the number, attributes and location of vehicle occupants were known. This can be used to provide a climate control system tailored to each occupant, for example, or the system can be turned off for certain seat locations if there are no occupants present at those locations.
U.S. Pat. No. 5,878,809 to Heinle, describes an air-conditioning system for a vehicle interior comprising a processor, seat occupation sensor devices, and solar intensity sensor devices. Based on seat occupation and solar intensity data, the processor provides the air-conditioning control of individual air-conditioning outlets and window-darkening devices which are placed near each seat in the vehicle. The additional means suggested include a residual air-conditioning function device for maintaining air conditioning operation after vehicle ignition switch-off, which allows maintaining specific climate conditions after vehicle ignition switch-off for a certain period of time provided at least one seat is occupied. The advantage of this design is the allowance for occupation of certain seats in the vehicle. The drawbacks include the lack of some important sensors of vehicle interior and environment condition (such as temperature or air humidity). It is not possible to set climate conditions individually at locations of each passenger seat.
U.S. Pat. No. 6,454,178 to Fusco, et al. describes an adaptive controller for an automotive HVAC system which controls air temperature and flow at each of locations that conform to passenger seats based on individual settings manually set by passengers at their seats. If the passenger corrects manual settings for his location, this information will be remembered, allowing for climate conditions taking place at other locations and further, will be used to automatically tune the air temperature and flow at the locations allowing for climate conditions at other locations. The device does not use any sensors of the interior vehicle conditions or the exterior environment, nor any seat occupation sensing.
14.9 Obstruction
In some cases, the position of a particular part of the occupant is of interest such as his or her hand or arm and whether it is in the path of a closing window or sliding door so that the motion of the window or door needs to be stopped. Most anti-trap systems, as they are called, are based on the current flow in a motor. When the window, for example, is obstructed, the current flow in the window motor increases. Such systems are prone to errors caused by dirt or ice in the window track, for example. Prior art on window obstruction sensing is limited to the Prospect Corporation anti-trap system described in U.S. Pat. No. 5,054,686 and U.S. Pat. No. 6,157,024. Anti trap systems are discussed in U.S. patent application Ser. No. 10/152,160 filed May 21, 2002, now abandoned.
14.10 Rear Impacts
The largest use of hospital beds in the United States is by automobile accident victims. The largest use of these hospital beds is for victims of rear impacts. The rear impact is the most expensive accident in America. The inventions herein teach a method of determining the position of the rear of the occupants head so that the headrest can be adjusted to minimize whiplash injuries in rear impacts.
14.11 Combined with SDM and Other Systems
The above applications illustrate the wide range of opportunities, which become available if the identity and location of various objects and occupants, and some of their parts, within the vehicle are known. Once the system is operational, it would be logical for the system to also incorporate the airbag electronic sensor and diagnostics system (SDM) since it needs to interface with SDM anyway and since they could share computer capabilities, which will result in a significant cost saving to the auto manufacturer. For the same reasons, it would be logical for a monitoring system to include the side impact sensor and diagnostic system. As the monitoring system improves to where such things as the exact location of the occupants' ears and eyes can be determined, even more significant improvements to the entertainment system become possible through the use of noise canceling sound, and the rear view mirror can be automatically adjusted for the driver's eye location. Another example involves the monitoring of the driver's behavior over time, which can be used to warn a driver if he or she is falling asleep, or to stop the vehicle if the driver loses the capacity to control it.
15. Definitions
Preferred embodiments of the invention are described below and unless specifically noted, it is the applicants' intention that the words and phrases in the specification and claims be given the ordinary and accustomed meaning to those of ordinary skill in the applicable art(s). If the applicants intend any other meaning, they will specifically state they are applying a special meaning to a word or phrase.
Likewise, applicants' use of the word “function” here is not intended to indicate that the applicants seek to invoke the special provisions of 35 U.S.C. §112, sixth paragraph, to define their invention. To the contrary, if applicants wish to invoke the provisions of 35 U.S.C. §112, sixth paragraph, to define their invention, they will specifically set forth in the claims the phrases “means for” or “step for” and a function, without also reciting in that phrase any structure, material or act in support of the function. Moreover, even if applicants invoke the provisions of 35 U.S.C. §112, sixth paragraph, to define their invention, it is the applicants' intention that their inventions not be limited to the specific structure, material or acts that are described in the preferred embodiments herein. Rather, if applicants claim their inventions by specifically invoking the provisions of 35 U.S.C. §112, sixth paragraph, it is nonetheless their intention to cover and include any and all structure, materials or acts that perform the claimed function, along with any and all known or later developed equivalent structures, materials or acts for performing the claimed function.
“Pattern recognition” as used herein will generally mean any system which processes a signal that is generated by an object (e.g., representative of a pattern of returned or received impulses, waves or other physical property specific to and/or characteristic of and/or representative of that object) or is modified by interacting with an object, in order to determine to which one of a set of classes that the object belongs. Such a system might determine only that the object is or is not a member of one specified class, or it might attempt to assign the object to one of a larger set of specified classes, or find that it is not a member of any of the classes in the set. The signals processed are generally a series of electrical signals coming from transducers that are sensitive to acoustic (ultrasonic) or electromagnetic radiation (e.g., visible light, infrared radiation, capacitance or electric and/or magnetic fields), although other sources of information are frequently included. Pattern recognition systems generally involve the creation of a set of rules that permit the pattern to be recognized. These rules can be created by fuzzy logic systems, statistical correlations, or through sensor fusion methodologies as well as by trained pattern recognition systems such as neural networks, combination neural networks, cellular neural networks or support vector machines.
A trainable or a trained pattern recognition system as used herein generally means a pattern recognition system that is taught to recognize various patterns constituted within the signals by subjecting the system to a variety of examples. The most successful such system is the neural network used either singly or as a combination of neural networks. Thus, to generate the pattern recognition algorithm, test data is first obtained which constitutes a plurality of sets of returned waves, or wave patterns, or other information radiated or obtained from an object (or from the space in which the object will be situated in the passenger compartment, i.e., the space above the seat) and an indication of the identify of that object. A number of different objects are tested to obtain the unique patterns from each object. As such, the algorithm is generated, and stored in a computer processor, and which can later be applied to provide the identity of an object based on the wave pattern being received during use by a receiver connected to the processor and other information. For the purposes here, the identity of an object sometimes applies to not only the object itself but also to its location and/or orientation in the passenger compartment. For example, a rear facing child seat is a different object than a forward facing child seat and an out-of-position adult can be a different object than a normally seated adult. Not all pattern recognition systems are trained systems and not all trained systems are neural networks. Other pattern recognition systems are based on fuzzy logic, sensor fusion, Kalman filters, correlation as well as linear and non-linear regression. Still other pattern recognition systems are hybrids of more than one system such as neural-fuzzy systems.
The use of pattern recognition, or more particularly how it is used, is important to the instant invention. In the above-cited prior art, except in that assigned to the current assignee, pattern recognition which is based on training, as exemplified through the use of neural networks, is not mentioned for use in monitoring the interior passenger compartment or exterior environments of the vehicle in all of the aspects of the invention disclosed herein. Thus, the methods used to adapt such systems to a vehicle are also not mentioned.
A pattern recognition algorithm will thus generally mean an algorithm applying or obtained using any type of pattern recognition system, e.g., a neural network, sensor fusion, fuzzy logic, etc.
To “identify” as used herein will generally mean to determine that the object belongs to a particular set or class. The class may be one containing, for example, all rear facing child seats, one containing all human occupants, or all human occupants not sitting in a rear facing child seat, or all humans in a certain height or weight range depending on the purpose of the system. In the case where a particular person is to be recognized, the set or class will contain only a single element, i.e., the person to be recognized.
To “ascertain the identity of” as used herein with reference to an object will generally mean to determine the type or nature of the object (obtain information as to what the object is), i.e., that the object is an adult, an occupied rear facing child seat, an occupied front facing child seat, an unoccupied rear facing child seat, an unoccupied front facing child seat, a child, a dog, a bag of groceries, a car, a truck, a tree, a pedestrian, a deer etc.
An “object” in a vehicle or an “occupying item” of a seat may be a living occupant such as a human or a dog, another living organism such as a plant, or an inanimate object such as a box or bag of groceries or an empty child seat.
A “rear seat” of a vehicle as used herein will generally mean any seat behind the front seat on which a driver sits. Thus, in minivans or other large vehicles where there are more than two rows of seats, each row of seats behind the driver is considered a rear seat and thus there may be more than one “rear seat” in such vehicles. The space behind the front seat includes any number of such rear seats as well as any trunk spaces or other rear areas such as are present in station wagons.
An “optical image” will generally mean any type of image obtained using electromagnetic radiation including visual, infrared and radar radiation.
In the description herein on anticipatory sensing, the term “approaching” when used in connection with the mention of an object or vehicle approaching another will usually mean the relative motion of the object toward the vehicle having the anticipatory sensor system. Thus, in a side impact with a tree, the tree will be considered as approaching the side of the vehicle and impacting the vehicle. In other words, the coordinate system used in general will be a coordinate system residing in the target vehicle. The “target” vehicle is the vehicle that is being impacted. This convention permits a general description to cover all of the cases such as where (i) a moving vehicle impacts into the side of a stationary vehicle, (ii) where both vehicles are moving when they impact, or (iii) where a vehicle is moving sideways into a stationary vehicle, tree or wall.
“Out-of-position” as used for an occupant will generally mean that the occupant, either the driver or a passenger, is sufficiently close to an occupant protection apparatus (airbag) prior to deployment that he or she is likely to be more seriously injured by the deployment event itself than by the accident. It may also mean that the occupant is not positioned appropriately in order to attain the beneficial, restraining effects of the deployment of the airbag. As for the occupant being too close to the airbag, this typically occurs when the occupant's head or chest is closer than some distance such as about 5 inches from the deployment door of the airbag module. The actual distance where airbag deployment should be suppressed depends on the design of the airbag module and is typically farther for the passenger airbag than for the driver airbag.
“Transducer” or “transceiver” as used herein will generally mean the combination of a transmitter and a receiver. In come cases, the same device will serve both as the transmitter and receiver while in others two separate devices adjacent to each other will be used. In some cases, a transmitter is not used and in such cases transducer will mean only a receiver. Transducers include, for example, capacitive, inductive, ultrasonic, electromagnetic (antenna, CCD, CMOS arrays), electric field, weight measuring or sensing devices. In some cases, a transducer may comprise two parts such as the plates of a capacitor or the antennas of an electric field sensor. Sometimes, one antenna or plate will communicate with several other antennas or plates and thus for the purposes herein, a transducer will be broadly defined to refer, in most cases, to any one of the plates of a capacitor or antennas of a field sensor and in some other cases a pair of such plates or antennas will comprise a transducer as determined by the context in which the term is used.
“Adaptation” as used here will generally represent the method by which a particular occupant sensing system is designed and arranged for a particular vehicle model. It includes such things as the process by which the number, kind and location of various transducers is determined. For pattern recognition systems, it includes the process by which the pattern recognition system is designed and then taught or made to recognize the desired patterns. In this connection, it will usually include (1) the method of training when training is used, (2) the makeup of the databases used, testing and validating the particular system, or, in the case of a neural network, the particular network architecture chosen, (3) the process by which environmental influences are incorporated into the system, and (4) any process for determining the pre-processing of the data or the post processing of the results of the pattern recognition system. The above list is illustrative and not exhaustive. Basically, adaptation includes all of the steps that are undertaken to adapt transducers and other sources of information to a particular vehicle to create the system that accurately identifies and/or determines the location of an occupant or other object in a vehicle.
For the purposes herein, a “neural network” is defined to include all such learning systems including cellular neural networks, support vector machines and other kernel-based learning systems and methods, cellular automata and all other pattern recognition methods and systems that learn. A “combination neural network” as used herein will generally apply to any combination of two or more neural networks as most broadly defined that are either connected together or that analyze all or a portion of the input data.
A “morphological characteristic” will generally mean any measurable property of a human such as height, weight, leg or arm length, head diameter, skin color or pattern, blood vessel pattern, voice pattern, finger prints, iris patterns, etc.
A “wave sensor” or “wave transducer” is generally any device which senses either ultrasonic or electromagnetic waves. An electromagnetic wave sensor, for example, includes devices that sense any portion of the electromagnetic spectrum from ultraviolet down to a few hertz. The most commonly used kinds of electromagnetic wave sensors include CCD and CMOS arrays for sensing visible and/or infrared waves, millimeter wave and microwave radar, and capacitive or electric and/or magnetic field monitoring sensors that rely on the dielectric constant of the object occupying a space but also rely on the time variation of the field, expressed by waves as defined below, to determine a change in state.
A “CCD” will be defined to include all devices, including CMOS arrays, APS arrays, QWIP arrays or equivalent, artificial retinas and particularly HDRC arrays, which are capable of converting light frequencies, including infrared, visible and ultraviolet, into electrical signals. The particular CCD array used for many of the applications disclosed herein is implemented on a single chip that is less than two centimeters on a side. Data from the CCD array is digitized and sent serially to an electronic circuit (at times designated 120 herein) containing a microprocessor for analysis of the digitized data. In order to minimize the amount of data that needs to be stored, initial processing of the image data takes place as it is being received from the CCD array, as discussed in more detail above. In some cases, some image processing can take place on the chip such as described in the Kage et al. artificial retina article referenced above.
The “windshield header” as used herein includes the space above the front windshield including the first few inches of the roof.
A “sensor” as used herein is the combination of two transducers (a transmitter and a receiver) or one transducer which can both transmit and receive. The headliner is the trim which provides the interior surface to the roof of the vehicle and the A-pillar is the roof-supporting member which is on either side of the windshield and on which the front doors are hinged.
An “occupant protection apparatus” is any device, apparatus, system or component which is actuatable or deployable or includes a component which is actuatable or deployable for the purpose of attempting to reduce injury to the occupant in the event of a crash, rollover or other potential injurious event involving a vehicle